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Data Scientist \n \n Position: Data Scientist \n \n Type: Contractor \n \n Compensation: $245–$280/hour \n \n Location: Remote \n \n About the Opportunity \n micro1 is partnering with a leading AI lab to engage experienced Data Scientists and quantitative professionals from top companies. In this role, you will apply your expertise in statistics, machine learning, experimentation, data analysis, and quantitative reasoning to evaluate and improve the capabilities of advanced AI systems. \n You will work on expert-level data science problems, assess AI-generated solutions, identify methodological and statistical weaknesses, and provide structured feedback that helps models reason more accurately and effectively. \n Responsibilities \n\n • Evaluate AI-generated outputs across data science, statistics, machine learning, and quantitative reasoning problems.\n, • Create expert-level prompts and datasets designed to assess advanced quantitative capabilities.\n, • Develop accurate reference solutions for complex data science and statistical problems.\n, • Identify flawed methodologies, statistical errors, and weaknesses in quantitative reasoning.\n, • Assess the validity and quality of AI-generated analytical approaches.\n, • Review model outputs for technical accuracy, logical consistency, and sound statistical reasoning.\n, • Provide structured, actionable feedback to improve AI model performance.\n, • Apply strong quantitative judgment when evaluating experimental designs, analytical methods, and data-driven conclusions.\n, • Communicate technical findings and statistical concepts clearly and precisely.\n\n Required Qualifications \n\n • At least 1 year of professional experience at a top company in technology, finance, research, or a comparable environment.\n, • At least part of the qualifying professional experience must have been within the past 7 years.\n, • Strong expertise in data science, statistics, machine learning, or quantitative analysis.\n, • Undergraduate degree from a top-ranked university.\n, • Strong analytical and quantitative reasoning abilities.\n, • Ability to evaluate complex statistical and machine-learning methodologies.\n, • Clear written communication of technical and statistical concepts.\n, • Ability to identify subtle errors in quantitative reasoning and analytical approaches.\n, • Professional proficiency in English.\n\n Preferred Qualifications \n\n • Professional experience combining Python, machine learning, statistics, and data analysis.\n, • Experience with Pandas and other data science tools.\n, • Experience with experimentation and experimental design.\n, • Strong understanding of data modeling and quantitative methods.\n, • Experience developing analytical datasets or benchmark problems.\n, • Background in quantitative roles within technology, finance, or research organizations.\n, • Experience evaluating technical or AI-generated outputs.\n, • Strong ability to explain complex quantitative concepts clearly and concisely.\n\n Compensation \n\n • $245–$280 per hour\n, • Contractor engagement\n, • Fully remote\n, • Expert-level work supporting AI evaluation and quantitative reasoning\n\n Eligibility \n\n • Candidates should have at least 1 year of experience working at a top company in technology, finance, research, or a related field.\n, • At least part of this experience should have been obtained within the past 7 years.\n, • Undergraduate degree from a top-ranked university.\n, • Candidates should be based in an English-speaking country.\n, • Strong written English and technical communication skills are required.\n\n Application Process \n\n • Submit your application highlighting your Data Science and quantitative experience.\n, • Detail your professional experience at relevant technology, finance, or research organizations.\n, • Highlight your expertise in statistics, machine learning, experimentation, and quantitative analysis.\n, • Provide information about your academic background and relevant technical skills.\n, • Selected candidates will be considered based on their quantitative expertise, professional background, and project fit.\n\n

Data Science & AI Instructor \n PE-Backed Data & AI Consulting Firm \n Build. Teach. Deploy \n \n 📍London, Hybrid \n 💰£90k - £120k plus bonus \n \n We are partnered with a PE Backed global Data & AI Consulting firm looking to completely re-imagine how they train and deploy their talent pools. \n \n With aspirations to reach Unicorn status within 3 years, you'll be joining a rocket ship already successfully disrupting the data and AI consulting market. \n \n You’ll start by helping shape a new generation of engineers — people learning how to build properly across data, AI, and modern systems, teaching what actually works in production, based on your own commercial experience. \n \n Then your role evolves. \n \n As those engineers move into client environments, you go with them — not as a trainer, but as a consultant. You’ll stay hands-on, work directly with end clients, and take ownership of delivery. You’ll lead from the front, guiding both the technical direction and the people you’ve helped develop. \n \n It’s a deliberate blend: build capability, then deploy it. \n \n The people who tend to lean into this are engineers with a strong foundation in AI, data, or backend systems who’ve already operated in consulting or client-facing environments. They’ve built real systems, understand the gap between theory and production, and naturally find themselves mentoring others — whether that’s through workshops, internal training, or just being the person others go to when things get complex. \n \n You don’t need to have been a full-time instructor. But you do need to care about how things are built, how they’re taught, and how they actually land in the real world. \n \n What makes this different is that you’re not stepping away from engineering to teach, and you’re not stuck in delivery without broader impact. You get both. You help shape how people are trained, and then you see that training hold up — or break — in real client environments, and refine it accordingly. \n \n If you’re starting to enjoy the mentoring side of engineering, but don’t want to lose the technical edge or the pace of real-world delivery, this is a pretty rare way to do both without compromise. \n \n Skills & Experience Required \n\n • Educated to degree level in a STEM subject; Mathematics, Statistics, Engineering, Chemistry, Physics, Computer Science, Machine Learning\n, • A commercial background in building and delivering data science and AI solutions end to end\n, • Ability to lead teach and deploy teams of engineers, data scientists and AI engineers onsite with end clients - ideally with some formal experience as an instructor from the likes of Kubrick, Brainstation, CodeFirstGirls, General Assembly, LE Wagon, Corndell, Ten10, La Fosse Academy etc.\n, • Strong consulting skills, ability to work directly with end customers on shaping data and AI solutions, overseeing delivery from deployed teams\n

JOB DESCRIPTION \n POSITION: Pricing Manager \n LOCATION: London/ flexible hybrid working \n \n About the Opportunity \n This is an exciting opportunity to join our client’s wider Underwriting team, as their new Pricing Manager, you’ll be a key figure in driving the evolution and growth, you’ll support and innovate processes. \n \n In this role you’ll use your deep expertise in market pricing and pricing optimisation to support their Pricing strategy by monitoring and analysing market trends and making the best of your unique skill set across market pricing, and loss ratio analysis to deliver actionable insight to the business. \n \n You’ll be at the heart of the Underwriting team, reporting to their Head of Pricing and building strong relationships in Underwriting, Actuarial, Finance and Marketing teams. \n \n Your Focus \n\n • Work closely with their Head of Pricing to deliver pricing strategy, deputising where needed\n, • Lead the development and refinement of pricing strategy in collaboration with the Head of Pricing, providing leadership and guidance to the pricing team\n, • Own market pricing activities including development of their demand, elasticity, and market pricing models and own and develop their pricing optimisation framework\n, • Providing inputs into the management and development of their lifetime value modelling and multi-year price optimisation models and strategic approach\n, • Monitor market trends and extract insight on competitor benchmarking to make rate recommendations\n, • Build a strong relationship with marketing and keep the business informed of their competitive position and conversion performance in their trading meetings\n\n \n What they’re Looking For \n\n • Ideally, you’ll already be a Pricing Manager or experienced senior analyst with technical pricing skills looking to step up\n, • You have strong commercial experience in a pricing role, preferably direct or aggregator-led personal lines insurance\n, • You’ll be an expert in predictive modelling and price optimisation with exposure to the latest emerging techniques in these domains such as machine learning and AI\n, • You’re up to date with technical developments in the insurance industry and best practice in actuarial methods\n, • You're a confident user of pricing tools, systems, and languages such as Python, SQL, Earnix, Radar or similar\n, • Owing to the nature of the role, they will need you to have a degree-level qualification (or equivalent) in Mathematics, Science, Engineering, or a related degree, with a minimum of a 2:1 classification\n\n

We are seeking a Senior Market Risk Analyst to join a global energy trading organisation in London. \n \n The role focuses on daily analysis of Structured Products trading activity, including reporting on positions and P&L, while providing support across other desks such as Gas, Crude Oil Derivatives, LNG, and Power & Emissions. You will also contribute to Market Risk projects, including covering reporting responsibilities as needed. \n \n The team is highly focused on automation and continuous improvement, with a strong emphasis on developing tools to enhance efficiency and analytics. This includes building solutions to support front office trading using techniques such as machine learning and artificial intelligence, with opportunities to contribute directly to these initiatives. \n \n Operating within global energy markets, the organisation is active across crude oil, refined products, and biofuels, with an international presence spanning multiple regions. It plays a key role in trading, logistics, and sourcing across both traditional and lower-carbon energy sectors, with an increasing focus on sustainability and the evolving energy landscape. \n \n Main Responsibilities \n\n • Preparing and reviewing daily P&L and risk reports, monitoring limits, and proactively resolving issues in coordination with relevant teams.\n, • Supporting front office in obtaining approval for new and non-standard products.\n, • Assisting in identifying significant risks within the business and ensuring transparency to senior management.\n, • Providing information and commentary for bi-weekly Risk Committee meetings.\n, • Reviewing and approving relevant changes to the main ETRM system (Endur).\n, • Ensuring compliance with trading procedures and controls and supporting internal and external audit requests when required.\n, • Participating in the enhancement of reporting and development of reporting systems.\n\n \n Skills and Experience Required \n\n • University degree in a numerate discipline (e.g. economics, mathematics, science, finance, engineering or similar).\n, • Relevant experience in a market risk role within commodity trading companies or financial institutions.\n, • Strong knowledge of risk metrics such as VaR, stress testing, and scenario analysis.\n, • Good understanding of derivatives and options.\n, • Strong knowledge of MS Office (especially Excel and VBA); SQL and Python are advantageous.\n, • Knowledge of the Endur ETRM system is an advantage.\n, • Analytical mindset with strong numerical skills.\n, • Strong organisational skills with attention to detail and ability to meet tight deadlines.\n, • Strong communication skills, with the ability to engage effectively with senior management and stakeholders.\n\n

Senior Data Scientist / Analyst – 6 Month Contract \n 📍 London – 3 days, 2 days remote \n 💰 £540 per day inside IR35 \n 📅 6-month contract (Extendable) \n \n We are looking for an experienced, hands-on Senior Data Scientist / Analyst to join a leading international financial technology business on an initial 6-month contract. \n \n The organisation operates at significant scale across multiple international markets, using data, technology and analytics to help consumers make better financial decisions. This is a highly autonomous role supporting the UK and Canadian markets, with responsibility for keeping critical analytics, data pipelines, production models and regulatory reporting running reliably. \n This is not a research or greenfield modelling role. We're looking for someone who is comfortable taking ownership of existing BAU processes, production models and data pipelines, troubleshooting issues and delivering against real business and regulatory deadlines. \n You'll work closely with Product, Marketing, Engineering, Business Development, Compliance and Member Support teams, translating complex data and technical issues into clear business outcomes. \n \n What you'll be doing \n Analytics & Business Intelligence \n\n • Monitor international revenue performance across the UK and Canada, investigating anomalies and identifying early indicators of revenue movement.\n, • Support partner monitoring and escalations, including offer setup, recommender/lookalike administration, partner click-report issues and ranking changes.\n, • Monitor email campaign performance, investigating anomalies, send failures, re-targeting opportunities and churn drivers.\n, • Support experimentation and A/B testing, including experiment monitoring, analysis and recommendations.\n, • Investigate data-quality issues across tracking, partner feeds and upstream data sources.\n, • Support member and regulatory data requests, including DSAR/RTBF requests, complaints data and FCA regulatory reporting.\n, • Monitor marketplace and partner rankings.\n, • Represent Analytics in business reviews and cross-functional forums, translating technical findings for non-technical stakeholders.\n\n \n Data Pipelines & ETL \n A key part of this role is understanding how data moves through the organisation and being able to troubleshoot issues when things go wrong. \n You'll be expected to: \n\n • Work hands-on with ETL (Extract, Transform, Load) processes and data pipelines.\n, • Extract and transform data from multiple sources for analytics and machine learning purposes.\n, • Investigate and resolve pipeline failures, data-feed issues and tracking gaps.\n, • Identify how upstream data-quality issues affect reporting and production models.\n, • Work with Engineering and other technical teams to resolve data issues.\n, • Validate data used by production models and reporting.\n, • Maintain reliable, repeatable data processes with appropriate monitoring and documentation.\n\n \n Data Science & Machine Learning \n\n • Maintain the existing suite of production ML models, including scheduled refreshes, retraining and redeployment.\n, • Monitor model performance and identify potential model drift or degradation.\n, • Troubleshoot issues affecting model inputs, pipelines and outputs.\n, • Perform data-quality checks on model inputs and production pipelines.\n, • Support partner-ranking changes and credit-model requirements in Canada.\n, • Ensure models and associated processes remain reliable without unnecessarily rebuilding them from scratch.\n, • Document and hand over models, pipelines, monitoring and reporting to the permanent team at the end of the contract.\n\n \n What we're looking for \n We're looking for an experienced hands-on Data Scientist who can operate independently in a production environment. \n \n Essential \n\n • 5+ years' experience in Data Science and/or advanced analytics.\n, • Proven experience working with production machine-learning models.\n, • Hands-on experience maintaining, monitoring, refreshing and troubleshooting existing ML models.\n, • Strong Python and SQL skills.\n, • Strong understanding of ETL, data pipelines and data transformation.\n, • Experience troubleshooting pipeline failures, data feeds and data-quality issues.\n, • Comfortable working with existing codebases and production environments rather than only building new solutions.\n, • Experience with model performance monitoring and/or model drift.\n, • Strong understanding of data quality and its impact on analytics and ML.\n, • Ability to take ownership of BAU processes with minimal supervision.\n, • Excellent communication skills, with the ability to explain technical issues clearly to business stakeholders.\n, • Comfortable working across Product, Engineering, Marketing, Compliance and Commercial teams.\n, • Degree or equivalent experience in Data Science, Computer Science, Mathematics, Statistics, Physics or another quantitative discipline.\n\n \n Desirable \n\n • Experience within financial services, fintech, credit, insurance or another regulated environment.\n, • Experience with FCA or other regulatory reporting.\n, • Experience working with revenue, customer, partner or commercial analytics.\n, • Contract or consulting experience working to fixed deadlines.\n, • Experience using AI tools such as Claude Code, OpenAI or similar to improve productivity and automate day-to-day workflows.\n, • Familiarity with agentic AI workflows.\n\n \n This role will suit someone who enjoys owning problems end-to-end. \n You'll need to be comfortable receiving an issue such as: \n "Revenue has dropped unexpectedly — is this a genuine business movement or a data problem?" \n and working through the data, pipelines, models and stakeholders to establish what's happening and provide an answer. \n \n You won't have a large team of people underneath you to do the investigation. You'll be expected to get into the data yourself, troubleshoot issues and keep the operation moving. \n \n If you enjoy being the person who understands how the data works, spots when something isn't right and can fix it, this could be a very good fit. \n \n If you're an experienced Senior Data Scientist with strong Python, SQL, ETL/data pipeline and production ML experience, we'd be keen to hear from you. \n

Navigator – London (Hybrid) \n Chief Product Officer \n Executive | Full-time | Reports to CEO \n Where We Are and Where We're Going \n Navigator is a performance media agency specialising in travel. We run campaigns globally across paid social, Google Ads, and programmatic for travel brands and agencies. We have scaled the business, work with some of the biggest brands and agencies in the world, and have partnerships with more than 20 of the world's largest travel booking platforms. \n We are transforming into the first, and only, true commerce media network in travel—a standalone network at the scale of Uber Advertising, built on first-party data that no one else has. Our ambition is to move from a service business that manually activates campaigns to a programmatic-first network that operates autonomously at scale for both endemic and non-endemic advertisers around the world. \n The two biggest challenges in commerce media today are fragmentation and standardisation. Navigator is being built to solve both by creating a unified network with consistent data, measurement, and activation across every channel, powered by more than two billion first-party data signals. We are at an exciting inflection point. The network is in its early stages, our machine learning foundations are being established, and advertising spend is already live. This is an opportunity to build something unique, leave a lasting impact on global advertising, and lead the product strategy behind a business that is already embracing agentic media buying. \n The Role \n The Chief Product Officer has a dual mandate. The first responsibility is to harness AI and agentic automation to increase productivity, output, and value across the existing agency operation, enabling the team to execute campaigns at a level and scale that would otherwise require a much larger workforce. The second responsibility is to build Navigator's AI-native, programmatic-first commerce media network. Both objectives must progress simultaneously. The current agency business must not be left behind; instead, it will be automated, evolved, and ultimately absorbed into the network. The CPO will own this transformation from end to end. \n Product Philosophy \n Navigator's product philosophy is based on an agent-to-tools architecture comprising foundational machine learning and a curated ecosystem of AI technologies. The first layer is an AI-native media workflow and orchestration platform capable of planning, activating, pacing, and optimising campaigns across DSPs, SSPs, RTB, Meta, TikTok, and other channels with minimal manual intervention. The second layer is an intelligence engine that continuously optimises campaigns, delivers real-time insights, and extracts value from more than two billion first-party data signals to create the most valuable audience and data products available to brands seeking to reach travellers. \n Key Responsibilities \n The immediate priority is automating the existing agency operation across Meta, TikTok, and Google Ads. The Chief Product Officer will identify friction throughout campaign workflows, including briefing, setup, trafficking, optimisation, and reporting, and implement AI-powered agentic workflows that reduce manual effort while increasing scale, speed, consistency, and accuracy. They will improve the client experience through faster reporting and richer performance insights without increasing operational overhead. They will also design an automation architecture based on an MCP-first approach that allows tools to be replaced easily, new agents to be introduced rapidly, and the platform to evolve with changing technology. \n The CPO will own Navigator's agentic media buying roadmap, building on existing partnerships with Scope3 and Kargo's Kera platform to transform early innovation into a scalable, differentiated product. They will define the balance between internally developed capabilities and partner technologies, creating an integrated agent-to-tools ecosystem. They will lead development towards fully autonomous campaign planning, activation, pacing, and optimisation while establishing the machine learning foundations required for audience segmentation, bid optimisation, frequency management, and predictive performance modelling. This capability will become a compelling client proposition that clearly differentiates Navigator from platforms, agencies, and holding companies. \n The role also includes leading the company's transition from predominantly paid social activation to a programmatic-first commerce media network. While Meta and TikTok will remain core revenue channels, the Chief Product Officer will scale Navigator's DSP, SSP, and RTB infrastructure into the network's primary activation capability. They will develop a unified activation layer that provides a consistent data model and buying interface across paid social and programmatic environments while managing strategic technical partnerships, API integrations, certifications, and evolving industry standards. \n Navigator's first-party data represents its competitive advantage. The Chief Product Officer will own the strategy, architecture, and commercial development of this data estate, ensuring it is structured, governed, and optimised for commercial value. They will oversee clean room integrations with partners to create a unified, privacy-safe view of traveller behaviour, enabling advanced audience modelling and targeting. They will build continuous campaign data feedback loops that ingest live performance data, improve optimisation models, and generate actionable client insights. They will also ensure privacy-by-design, regulatory compliance, and strong data governance are embedded throughout the platform. \n Measurement remains platform-agnostic. Navigator currently supports whichever measurement solutions clients or agencies require, and the Chief Product Officer will ensure seamless integration with third-party measurement providers while positioning the business to expand its own measurement capabilities as the network matures. \n Leadership \n The Chief Product Officer will build and lead the product and engineering organisation, recruiting and structuring teams capable of delivering the platform at scale. They will own the product roadmap, balancing priorities across agency automation, agentic media buying, programmatic infrastructure, and the data platform while making clear trade-off decisions. They will work closely with commercial teams to ensure product capabilities translate into compelling client propositions, support sales opportunities, and deliver measurable business outcomes. The role also includes managing AI and technology partnerships, evaluating new capabilities that strengthen the ecosystem, and representing product and technology strategy at board level by communicating architecture decisions, platform maturity, and build-versus-buy recommendations clearly to executives, investors, and stakeholders. \n About You \n The ideal candidate has significant product leadership experience within ad technology and has built or scaled programmatic infrastructure such as DSPs, SSPs, DMPs, or data marketplaces. They possess deep expertise in performance marketing across Meta and TikTok and understand campaign architecture, audience strategy, optimisation, and how to systematise media operations at scale. \n They have worked closely with machine learning and data science teams to deliver production AI models and understand where agentic AI can safely automate workflows and where human oversight remains essential. They have experience operating live service businesses while simultaneously building technology platforms and understand how to balance operational excellence with long-term product development. \n The successful candidate also has substantial experience working with first-party data and clean room technologies, including platforms such as AWS Clean Rooms, Snowflake, InfoSum, Habu, or equivalent solutions. They are a builder who is equally comfortable making architectural decisions and defining product roadmaps while operating in fast-moving environments with imperfect information. \n Commercial awareness is essential. The Chief Product Officer understands how product strategy influences revenue growth, customer retention, pricing, and market differentiation. They are also an excellent communicator who can present complex technical concepts clearly and confidently to boards, investors, clients, partners, and senior executives. \n Nice to Have \n Experience within a commerce media network, travel technology platform, or vertical data marketplace would be advantageous. Familiarity with agentic AI platforms such as Scope3, Kargo Kera, LangChain, AutoGen, or similar technologies would also be valuable, together with a clear perspective on their application to media workflow automation. An engineering background, including direct leadership of engineering teams, is desirable, as is experience guiding a business through the transition from founder-led product development to the more structured processes typically associated with Series A to Series B growth.

Bioinformatics Scientist (Microbial Genomics) \n \n London (On-site 4-5 days) | Up to £70,000 + Equity | Some flexibility for exceptional candidates \n \n We're working with a London-based BioAI company that holds one of the largest proprietary biodiversity datasets in the world. Backed by a major AI infrastructure company and fresh off a Series B, they've sampled environments across the globe and are sitting on billions of genes, a huge proportion of which are microbial, novel, and largely uncharacterised. \n \n This is frontier biology. They're mapping genetic data across 100M+ species with the goal of expanding known biology by orders of magnitude, and training foundation models on data that simply doesn't exist anywhere else. \n \n The Role \n You'll be working with large-scale microbial and metagenomic data that is messy, novel, and full of potential. The expectation is that you develop new methods and tools to make sense of it, not apply existing ones. You'll be building things, publishing things, and directly shaping how one of the richest biodiversity datasets in the world gets analysed and understood. \n \n Requirements \n\n • You have built a bioinformatics tool, method, or software package that other people can use. Published, open-sourced, or otherwise demonstrable. This is the single most important requirement. The role is fundamentally about developing new methods, so a track record of building is essential.\n, • Experience working with large-scale microbial or metagenomic data\n, • Strong programming skills (Python, R, or similar) oriented toward building software, not just writing analysis scripts\n, • Comfortable working with messy, real-world biological data that requires developing new approaches\n\n \n Preferences \n\n • Published tool or method in a peer-reviewed journal, or available on GitHub/PyPI/Bioconda\n, • Experience with pangenomics, metagenome binning, microbial community analysis, or functional annotation\n, • Familiarity with workflow managers (Nextflow, Snakemake) for deploying your own tools at scale\n, • Exposure to machine learning applied to biological data\n\n \n This role is on-site in London 4-5 days per week. International relocation support is available. \n

Data Scientist \n London (2 days per week) \n Up to £65,000 \n \n This is an opportunity to join a leading data and analytics consultancy working on a wide variety of predictive modelling projects across utilities, telecommunications, financial services and customer insight. You'll have the chance to take ownership of projects, work directly with stakeholders and apply Data Science techniques to solve real commercial challenges. \n \n The Company \n They are a well-established data and analytics consultancy that combines proprietary data assets with advanced analytical expertise to help organisations make better decisions. Their work focuses on customer intelligence, predictive modelling and analytics solutions that deliver measurable business outcomes. \n Working across multiple industries, they partner with clients to solve challenges around customer acquisition, retention, collections, marketing effectiveness and operational performance. Their teams combine industry expertise, analytics and modern data platforms to deliver impactful solutions. \n \n The Role \n As a Data Scientist, you will develop predictive models and analytical solutions that support client decision-making and customer strategy. \n Responsibilities include: \n\n • Building machine learning models across use cases including propensity to pay, customer acquisition, churn prediction, lifetime value and segmentation\n, • Developing classification, regression and clustering models using customer and transactional data\n, • Working closely with clients and stakeholders to understand business problems and define analytical approaches\n, • Leading data discovery sessions and gathering requirements from subject matter experts\n, • Presenting insights, recommendations and model outputs to both technical and non-technical audiences\n, • Monitoring, refining and retraining models to ensure ongoing performance\n, • Collaborating with analysts, project managers and industry specialists to deliver client projects\n, • Contributing to reports, dashboards and client presentations\n\n \n Your Skills & Experience \n\n • Strong commercial Data Science experience within predictive modelling\n, • Advanced Python and SQL skills\n, • Experience building classification, regression and clustering models from the ground up\n, • Strong understanding of model performance, validation and optimisation\n, • Confident communicating insights to technical and non-technical stakeholders\n, • Experience with modern cloud and data platforms such as Databricks, AWS, Azure or Snowflake\n, • Exposure to customer analytics, credit risk, collections, telecommunications or utilities is advantageous\n, • Comfortable taking ownership of projects and working independently\n\n \n What They Offer \n\n • Salary up to £65,000\n, • Hybrid working with two days per week in London\n, • Exposure to a broad range of Data Science and machine learning projects\n, • Direct client engagement and stakeholder exposure\n, • Access to modern cloud and analytics technologies\n, • Strong opportunities for technical and professional development\n, • Collaborative and supportive working environment\n\n

Data Scientist \n \n Vacancy Information \n\n • Location: London, UK\n, • Salary: Competitive\n, • Working Pattern: Hybrid, 3 days per week in the office\n, • Contract Type: Permanent\n, • Working Hours: Monday to Friday\n\n \n At TTC, we are Enriching lives by connecting people and places. \n For over 100 years, we’ve been bringing the world closer together by crafting journeys that create lasting memories, lifelong friendships and meaningful cultural connections. Across more than 70 countries and our award-winning brands, we design and deliver travel experiences that go beyond sightseeing - they change perspectives. \n Behind every unforgettable journey is a passionate team making it happen. That’s where you come in. \n \n Our Values \n Five shared commitments shape how we work, and how we will work with you: \n\n • Value Every Voice. We put people first.\n, • Act with Integrity. We do what is right.\n, • Explore Beyond Boundaries. We are driven by curiosity.\n, • Own the Outcome. We take responsibility for our decisions.\n, • Succeed Together. We have each other's backs.\n\n \n The Role \n This is applied data science. You will use advanced analytics and machine learning to understand our customers better and solve problems that genuinely matter to the business, working with customer, booking, digital, marketing and behavioural data. \n You will work across segmentation, propensity, personalisation, retention, forecasting and customer lifetime value, with the space to explore and the support to grow. What matters here is not building technically interesting models, but connecting rigorous analytical work to decisions, actions and outcomes you can point to. You will sit alongside experienced data scientists, engineers and analysts in a capability that is being built and scaled right now. \n \n What Will You Do? \n\n • Turn customer and commercial challenges into structured analytical problems and testable hypotheses.\n, • Explore complex behavioural and transactional data to find what others have missed.\n, • Develop and evaluate statistical and machine learning models.\n, • Build segmentation, propensity, forecasting and personalisation solutions that reach real customers.\n, • Apply rigour to feature engineering, validation and model performance.\n, • Design and evaluate experiments to understand genuine impact.\n, • Work with Data Engineering to create reliable model inputs and productionise valuable solutions.\n, • Monitor solutions in the wild and keep improving them.\n, • Communicate findings clearly to both technical and business audiences.\n, • Contribute to data science standards, reproducibility and responsible AI practice.\n\n \n About You \n Essential \n\n • Strong professional experience in data science or advanced analytics.\n, • Advanced practical capability in Python and SQL.\n, • A strong grounding in statistics and machine learning.\n, • Experience developing and validating predictive models.\n, • Experience with customer, transactional, behavioural or digital data.\n, • Understanding of experimentation and statistical measurement.\n, • Analytical curiosity paired with pragmatic commercial judgement.\n, • The ability to explain complex analysis clearly and connect it to business action.\n\n Desirable \n\n • Exposure to segmentation, propensity, churn, forecasting, lifetime value or personalisation.\n, • Experience with Snowflake, cloud data science environments or production machine learning.\n, • Familiarity with responsible AI principles and reproducible practice.\n, • Experience in a global, multi-brand or multi-market business.\n, • Curiosity about travel, hospitality or global consumer businesses.\n\n \n Apply Now \n If you want to build your data science career on data this rich, we would like to hear from you. Apply today, and tell us about a problem you enjoyed solving. \n

We've been exclusively engaged by our client, a London-based AI-Native TechBio company, to find their next Director of Computational Biology. The company uses computational and experimental biology together to find new therapeutic targets in areas of high unmet medical need. Founded by a team of scientists and engineers who were frustrated by how disconnected "wet" and "dry" biology usually are, they've built their lab and software stack side by side from day one. Every computational model is grounded in data they generate themselves, and every experiment is informed by what the models find. \n \n About the Role \n We're looking for a Director of Computational Biology to build and lead a high-impact team at the intersection of biology, data science, and machine learning. You'll shape our computational strategy, translate complex biological questions into tractable analytical problems, and help drive discoveries from bench to insight. This is a rare opportunity to build a function from a position of real influence — setting scientific direction, hiring the team, and shaping how computation is embedded across the organisation. \n \n What You'll Do \n\n • Define and lead the computational biology strategy, aligning it with broader R&D and business goals\n, • Build, mentor, and grow a team of computational biologists, bioinformaticians, and ML scientists\n, • Partner closely with wet-lab biology, chemistry, clinical, and data engineering teams to embed computational thinking across the pipeline\n, • Drive the design and application of methods spanning genomics, multi-omics integration, structural biology, and/or machine learning for target discovery and validation\n, • Own the computational infrastructure, tooling, and data strategy that underpins the science\n, • Represent computational biology externally — with academic collaborators, investors, and scientific advisory boards\n, • Translate ambiguous biological problems into clear, well-scoped computational projects with measurable outcomes\n\n \n What We're Looking For \n\n • PhD in Computational Biology, Bioinformatics, Genomics, Computer Science, or a related field\n, • Significant experience leading computational biology or bioinformatics teams, ideally in biotech, pharma, or a research-intensive environment\n, • A strong publication record and/or a track record of computational work that directly influenced experimental or clinical decisions\n, • Deep fluency in at least one core area (e.g. genomics, proteomics, single-cell analysis, structural biology, or ML/AI applied to biology), with working knowledge across others\n, • Proven ability to build and scale teams, including hiring, mentoring, and setting technical direction\n, • Comfort operating at both a strategic level (roadmaps, cross-functional alignment) and a hands-on level when needed\n, • Excellent communication skills — able to make complex computational work legible to biologists, and biological nuance legible to computational colleagues\n\n \n Nice to Have \n\n • Experience working with large-scale multi-omics or clinical datasets\n, • Familiarity with cloud-based computational infrastructure (AWS/GCP) at scale\n, • Prior experience in a startup or scale-up environment\n, • Contributions to open-source scientific software\n\n

Senior Data Scientist \n \n Vacancy Information \n\n • Location: London, UK\n, • Salary: Competitive\n, • Working Pattern: Hybrid, 3 days per week in the office\n, • Contract Type: Permanent\n, • Working Hours: Monday to Friday\n\n \n \n At TTC, we are Enriching lives by connecting people and places. \n For over 100 years, we’ve been bringing the world closer together by crafting journeys that create lasting memories, lifelong friendships and meaningful cultural connections. Across more than 70 countries and our award-winning brands, we design and deliver travel experiences that go beyond sightseeing - they change perspectives. \n Behind every unforgettable journey is a passionate team making it happen. That’s where you come in. \n \n Our Values \n Five shared commitments shape how we work, and how we will work with you: \n\n • Value Every Voice. We put people first.\n, • Act with Integrity. We do what is right.\n, • Explore Beyond Boundaries. We are driven by curiosity.\n, • Own the Outcome. We take responsibility for our decisions.\n, • Succeed Together. We have each other's backs.\n\n \n The Role \n This is a role for someone who wants their models used, not admired. You will solve complex customer and commercial problems through advanced analytics, experimentation and machine learning, working with rich customer, booking, behavioural, marketing and digital data. \n The problem space is broad: segmentation, propensity, personalisation, customer value, retention, forecasting and commercial optimisation. Alongside hands-on work, you will shape analytical methodology, mentor other data scientists and help our most valuable models move from experiment into decisions that change what the business does. The data is rich, the questions are real and the appetite for answers is genuine. \n \n What Will You Do? \n\n • Lead complex data science initiatives from problem definition through modelling, validation and implementation.\n, • Build predictive and machine learning solutions across priority customer and commercial use cases.\n, • Apply advanced statistical techniques to uncover behaviour, patterns and commercial opportunity.\n, • Design rigorous experiments and measurement approaches that reveal genuine incremental impact.\n, • Set best practice in feature engineering, validation, reproducibility and model evaluation.\n, • Work with Data Engineering to productionise high-value analytical solutions.\n, • Guide model monitoring, drift management and ongoing performance.\n, • Turn sophisticated analysis into clear recommendations for senior decision-makers.\n, • Mentor data scientists and provide technical leadership across the team.\n, • Contribute to data science strategy, standards, governance and responsible AI practice.\n\n \n About You \n Essential \n\n • Significant experience in data science, applied data science or machine learning in a sophisticated commercial environment.\n, • Advanced capability in Python and SQL.\n, • Deep grounding in statistics, machine learning, experimentation and model validation.\n, • Solutions you can point to that delivered measurable customer or commercial impact.\n, • Strong experience across segmentation, propensity, lifetime value, personalisation or forecasting.\n, • Experience with large-scale behavioural, transactional or customer datasets.\n, • Understanding of production data science, MLOps and model monitoring.\n, • Commercial judgement and the ability to simplify complex technical findings.\n\n Desirable \n\n • Experience providing technical leadership, peer review or coaching to other data scientists.\n, • Exposure to Snowflake or another modern cloud data science environment.\n, • Experience contributing to responsible AI standards or governance.\n, • Experience in a global, multi-brand or multi-market business.\n, • Curiosity about travel, hospitality or global consumer businesses.\n\n \n Apply Now \n If you want your work to shape how millions of people experience travel, we would like to hear from you. Apply today, and tell us about a model that changed a decision. \n

Data Scientist, London/Oxford hybrid working \n \n Are you excited by the opportunity to use machine learning, NLP, and generative AI to help researchers discover knowledge faster and make better decisions? \n \n Would you enjoy turning complex scientific and business challenges into practical, production-ready AI solutions that create real user value? \n \n About our Team \n Our global team support products education electronic health records that introduce students to digital charting and prepare them to document care in today’s modern clinical environment. We have a very stable product that we’ve worked to get to and strive to maintain. Our team values trust, respect, collaboration, agility, and quality. \n \n About the Role \n In this role, you will design and build machine learning, NLP, and generative AI solutions that support scientific discovery, knowledge extraction, decision support, and intelligent content understanding. You will work with large-scale scientific content and data, applying the right techniques to solve complex problems and deliver reliable, production-ready systems. Working closely with cross-functional partners, you will help turn ambiguous challenges into measurable outcomes that improve how researchers discover and use knowledge. \n \n Responsibilities \n\n • Design and build machine learning, NLP, and generative AI systems for scientific discovery, knowledge extraction, decision support, and intelligent content understanding.\n, • Work with large-scale, complex, and heterogeneous data, including scientific publications, research datasets, knowledge graphs, ontologies, taxonomies, citations, metadata, and content from every scientific discipline.\n, • Apply the right technique to each problem, using approaches such as classification, regression, clustering, ranking, feature engineering, deep learning, embeddings, LLMs, retrieval, and generative AI.\n, • Develop capabilities for semantic search, information retrieval, entity extraction, content classification, recommendation, ranking, summarization, question answering, and evidence-grounded generation.\n, • Build, evaluate, fine-tune, prompt, and integrate models into robust production systems, while continuously improving quality, relevance, reliability, and user value.\n, • Write clean, tested, production-quality Python and contribute reusable data science components, packages, and scalable data pipelines for preprocessing, inference, experimentation, monitoring, and continuous improvement.\n, • Support deployment, monitoring, model maintenance, drift detection, automated retraining, and ongoing optimization of data science systems.\n, • Collaborate with engineering, product, UX, analytics, research, and domain experts, and communicate technical concepts, model behavior, insights, trade-offs, and recommendations clearly to technical and non-technical audiences.\n\n \n Requirements \n\n • Experience in data science, machine learning, artificial intelligence, NLP, statistics, applied mathematics, computer science, or a related quantitative area.\n, • Experience working with frontier LLMs such as OpenAI’s GPTs, Anthropic’s Claude, and Google’s Gemini, including fine-tuning LLMs and/or SLMs.\n, • Strong Python skills and a habit of writing clean, maintainable, well-tested code.\n, • A solid grasp of machine learning fundamentals, including supervised and unsupervised learning, feature engineering, model evaluation, model selection, and performance measurement.\n, • Experience working with structured, semi-structured, or unstructured data, especially large-scale text or content datasets.\n, • Familiarity with common data science and machine learning tools such as Pandas, NumPy, SciPy, Scikit-learn, PyTorch, TensorFlow, or Matplotlib.\n, • The ability to translate complex and ambiguous requirements into practical, measurable, data-driven solutions, with strong analytical thinking, problem-solving skills, and attention to quality.\n, • Clear communication skills, a collaborative approach to working with engineering, product, and business stakeholders, and a genuine interest in building production-ready systems that deliver real user value.\n\n \n Work in a Way That Works for You \n We promote a healthy work/life balance across the organisation. We offer an appealing working prospect for our people. With numerous wellbeing initiatives, shared parental leave, study assistance, and sabbaticals, we will help you meet your immediate responsibilities and your long-term goals. \n \n Working Pattern \n Working flexible hours - flexing the times when you work in the day to help you fit everything in and work when you are the most productive \n \n About the Business \n A global leader in information and analytics, we help researchers and healthcare professionals advance science and improve health outcomes for the benefit of society. Building on our publishing heritage, we combine quality information and vast data sets with analytics to support visionary science and research, health education and interactive learning, as well as exceptional healthcare and clinical practice. At Elsevier, your work contributes to the world's grand challenges and a more sustainable future. We harness innovative technologies to support science and healthcare to partner for a better world.

wn machine learning that drives decisions across a 4M+ member platform \n Build commercial models spanning retention, recommendations and customer growth \n Work directly with senior stakeholders in a growing Data Science team \n \n Up to £90,000 + 7% Bonus \n Hybrid | London (2 days/week) - Leicester office visit once a month included \n \n Join one of the UK's largest membership platforms, using machine learning to improve engagement, retention and commercial performance for over 4 million members. \n Working within a small, high-impact Data Science team, you'll develop models across retention, CLV, recommendations, search, forecasting and anomaly detection, partnering closely with Product, Marketing, CRM and Finance. \n \n The Role \n\n • Build retention, churn and CLV models\n, • Develop recommendation and search algorithms\n, • Create forecasting and marketing mix models\n, • Detect fraud, broken journeys and offer issues\n, • Design and evaluate A/B tests\n, • Translate business problems into scalable ML solutions\n, • Tech stack: Python, SQL, Databricks, dbt, MLflow\n\n \n Requirements \n\n • 5+ years' commercial Data Science experience\n, • Strong Python and SQL skills\n, • Experience with customer, marketing, ecommerce or loyalty data\n, • Background in retention, CLV, recommendations or experimentation\n, • Excellent stakeholder management\n, • Databricks, dbt or MLflow exposure is beneficial\n\n \n Why Join? \n\n • Up to £90,000 + 7% bonus\n, • Hybrid working (2 days/week)\n, • High commercial ownership and visibility\n, • Dedicated MLOps support\n, • Opportunity to shape strategy through machine learning\n\n \n If you're looking for a role where your models directly influence customer experience, commercial performance and strategic decision making, please apply below.

🚀 Company Overview \n \n AI is driving data center power consumption to more than double, from ~460 TWh today to a projected 1,000 TWh by 2030, roughly the electricity consumption of Japan! Hyperscalers and AI companies are racing to secure compute capacity, while new grid connections in key markets are queued years out. Meanwhile, capacity sits stranded in existing infrastructure, managed through outdated models that were never built to handle the power-dense workloads coming rapidly down the pike. \n \n At Zendo we're developing the operating layer that enables operators to get more value from every watt. Our Energy OS platform brings together operational data, energy intelligence, and proprietary load forecasting across the data center power stack to help operators access more capacity, sooner. \n \n We’ve been building at pace to match the urgency of the capacity crunch, with some great traction so far: \n \n\n • Raised $2M+ in pre-seed funding from Fly Ventures, Pact, and Octopus Ventures, with angels from Google and across the data centre industry.\n, • Live with several UK data centre customers, with a pipeline to grow across the market.\n, • A founding team combining deep energy, B2B software, and data centre infrastructure expertise — ex-Octopus Energy, Square, Meta.\n\n \n This is an opportunity to join us on the ground floor, work directly with the founders, and grow with the business as we build Zendo into a true category leader on the frontlines of an industry undergoing the largest infrastructure build-out in history. \n \n 📊 Your Role as Data Scientist \n \n You'll work directly with our Founding Engineer (ex-Meta infrastructure) and the founders to \n build the data and modelling foundation at the core of Zendo's platform. You will own the full data lifecycle — from raw data centre data through to the predictive models powering capacity optimisation and the real-time economic model. \n \n Examples of what you'll be working on: \n\n • Workload forecasting: improving Zendo's ability to predict data centre power demand accurately, building models that handle the complexity and variability of modern workloads.\n, • Capacity optimization models: sharpening the statistical rigour behind our capacity optimisation results, improving the quality and confidence of recommendations we deliver to operators.\n, • Real-time economic modeling: building a real-time economic model that connects capacity availability to commercial outcomes, unlocking workload optimisation capabilities.\n, • Model productionization: working with the engineering team to take models from development to production, ensuring they perform reliably on live customer data.\n\n \n 🎯 What We're Looking For \n\n • MS or higher in statistics or machine learning, or equivalent experience (3-5 years in the\n\n industry). \n\n • Experience building and evaluating predictive models — you care about accuracy and know how to measure it properly.\n, • Strong time-series background — you've worked with high-frequency, real-world data that's messy and incomplete.\n, • Experience taking models to production, not just building them in notebooks.\n, • Comfort working in a small team where you own ambiguous ML problems end-to-end.\n, • Strong communication skills — you can explain model behaviour and uncertainty to non- technical stakeholders.\n\n \n ✨ Nice to have: \n\n • Understanding of electrical or mechanical systems, energy markets, or data center operations.\n, • Quantitative expertise or experience with economic modeling and real-time market bidding (e.g., simulated quant work, market making).\n, • Experience working in fast-paced delivery environments, proven experience building MVPs quickly and scaling later.\n\n \n 🧠 Beyond the CV: \n\n • You're comfortable with ambiguity — the data won't always be clean and the problem won't always be well-defined.\n, • You think about the downstream commercial impact of your work, not just the technical output.\n, • You thrive in a 0→1 environment and take ownership end-to-end without waiting to be told what to do next.\n, • You're energised by working on a small team where your decisions have immediate, visible impact.\n\n \n 🎁 What We're Offering \n\n • A ground-floor, high-ownership role at a well-backed startup at one of the most exciting intersections in tech right now — AI compute and energy.\n, • Work directly with the founding team and a growing network of strategic advisors and investors.\n, • Access to a lovely co-working space in the heart of London’s Knowledge Quarter.\n, • Quarterly team offsites and socials.\n, • Competitive salary + equity.\n\n \n 📍 Location & Requirements \n\n • Hybrid: We work 1–2 days/week from co-working spaces in London (King's Cross).\n, • Right to Work: You must have the legal right to work in the UK. We are unfortunately unable to sponsor visas at this time.\n\n \n 👋 Ready to join the team? If you're excited about building the future of energy infrastructure for the AI era, we'd love to hear from you! \n \n Click the Easy Apply button below to submit your profile.

We are seeking a Global E-Commerce's Governance and Experience (GNE) is a global team responsible for ensuring a safe and trustworthy marketplace for not only our buyers, but also our sellers and creators . The Moderation Team is part of the GNE organization. Our mission is to create the most trustworthy E-commerce platform with a delightful service experience . We are looking for Moderation Quality Assurance Specialist role to analyse moderation quality performance, evaluating the delivery quality of BPO sites, provide indepth RCA for critical issues as well as the implementation of effective action plans . \n \n Key Responsibilities: \n\n • Content Review & Analysis\n, • Conduct comprehensive review and analysis of sellers, products, content and Intellectual Property Rights (IPR) to ensure compliance with platform policies\n, • Perform daily quality assessments of moderation decisions across multiple content categories\n, • Identify patterns and trends in content violations through systematic data analysis\n, • Review and evaluate the accuracy of content moderation decisions made by BPO teams or machine moderation\n, • Quality Assurance & Process Improvement\n, • Help build quality assessment processes and conduct quality assessment work by ensuring and evaluating the delivery quality of the sellers, products, IPR, and contents reviewed\n, • Participate in the development of quality inspection standards and continuously optimise the processes and platform\n, • Conduct root cause data analysis and provide insights and key actions to improve processes\n, • Develop and implement quality metrics and KPIs to measure moderation effectiveness\n, • Policy Enhancement & Compliance\n, • Enhance moderation policy and work closely with local operations and policy teams\n, • Provide recommendations for policy updates based on content review findings\n, • Ensure adherence to regional regulatory requirements and platform standards\n, • Stakeholder Management & Reporting\n, • Prepare detailed quality reports and analysis for management review\n, • Collaborate with cross-functional teams\n, • Conduct calibration sessions with BPO teams to ensure consistent application of moderation policies\n, • Root Cause Analysis & Action Planning\n, • Perform in-depth RCA (Root Cause Analysis) for critical moderation issues and provide detailed insights on quality gaps\n, • Develop and implement effective action plans to address identified quality issues\n, • Track and monitor the effectiveness of implemented corrective actions\n, • Create case studies and learning materials based on quality analysis findings\n\n \n Qualifications: \n Education & Experience \n\n • Bachelor's degree or above\n, • Minimum 3 years of hands on and in-depth experience in e-commerce safety and quality analysis is a must\n, • Proven experience in content moderation, quality assurance, or trust and safety operations\n, • Experience working with BPO teams preferred\n, • Language & Communication Skills\n, • Fluency in English is a must. Knowledge in another European languages is a plus.\n, • Excellent coordination skills and communication skills across multiple cross-functional teams to build plans and projects\n, • Strong written and verbal communication skills for reporting and stakeholder management\n, • Technical & Analytical Skills\n, • Ability to digest large data sets/policies in a cohesive and actionable manner\n, • Familiarity with office software such as Excel, Word, Power point, etc.\n, • Strong analytical skills with experience in data analysis and reporting\n, • Basic understanding of SQL or data visualization tools is a plus\n\n \n Atain (previously known as IGT Solutions) provides equal employment opportunities to all individuals based on job related qualifications and ability to perform a job, without regard to age, gender, gender identity, sexual orientation, race, color, religion, creed, national origin, disability, genetic information, veteran status, citizenship or marital status, and to maintain a non-discriminatory environment free from intimidation, harassment or bias based upon these groups. \n

\n Associate Analytics Consultant \n London (Hybrid – Monday to Thursday Office / Friday Remote) \n Up to £75,000 \n \n THE COMPANY \n This global data, analytics and technology business helps organisations make smarter lending decisions through market-leading credit data, analytics and consultancy. Working with banks, lenders, telecoms and other major organisations, they develop analytical solutions that improve customer acquisition, credit decisions and portfolio performance. Having recently migrated to the cloud and invested heavily in Python, it's an exciting time to join a business known for its strong culture and excellent staff retention. \n \n THE ROLE \n As an Associate Consultant within the Client Analytics team, you'll deliver consultancy projects for some of the UK's largest lenders and financial services organisations. Working directly with clients, you'll build credit scorecards, develop lending strategies and create statistical models using Credit Reference Agency (CRA) data to help businesses make better lending decisions. \n This is a highly commercial, client-facing position where you'll own analytical projects from discovery through to delivery, presenting insights and recommendations to senior stakeholders while balancing technical excellence with commercial impact. \n You'll be responsible for: \n\n • Developing acquisition and behavioural credit scorecards using CRA data\n, • Building statistical and machine learning models including logistic and linear regression\n, • Designing and implementing credit strategies for new and existing customer portfolios\n, • Analysing large datasets using SQL and Python (or SAS)\n, • Delivering analytical consultancy projects for external clients across multiple industries\n, • Presenting technical findings and commercial recommendations to senior stakeholders\n, • Supporting clients to improve lending decisions through data-driven insights\n\n The role covers the full modelling lifecycle, including sample design, performance analysis, reject analysis and strategy development. \n \n \n YOUR SKILLS AND EXPERIENCE \n You'll ideally have: \n\n • Experience developing credit scorecards within a credit risk environment\n, • Strong knowledge of Credit Reference Agency (CRA) data (Equifax, Experian or TransUnion)\n, • Credit risk experience across model development or strategy\n, • Strong SQL skills alongside Python or SAS (Python preferred)\n, • Experience with statistical modelling techniques such as logistic regression or machine learning\n, • Excellent communication skills with the ability to present to clients and senior stakeholders\n\n THE BENEFITS \n\n • Up to £75,000 salary\n, • Hybrid working (Monday-Thursday office, Fridays remote)\n, • Work with a wide range of clients across financial services, telecoms and beyond\n, • Opportunity to work on varied analytical consultancy projects rather than a single portfolio\n, • Modern cloud-based technology stack with increasing use of Python\n, • Strong career progression within a business known for long employee tenure\n, • Two-stage interview process with a fast turnaround\n\n \n HOW TO APPLY \n Please register your interest by sending your CV to Max Beadle at Harnham via the Apply link on this page.

JD.com (NASDAQ: JD and HKEX: 9618), also known as JINGDONG, has evolved from a pioneering e-commerce platform into a leading technology and service provider with supply chain at its core. Renowned for its supply chain innovation and excellence, the company has expanded into sectors including retail, technology, logistics, healthcare, and more, aiming to transform traditional business models with cutting-edge digital solutions. Know more about us: https://corporate.jd.com/ \n \n JD.com is seeking an experienced Technical Product Manager to join our growing technical team at Joybuy (https://www.joybuy.com/). Joybuy is JD.com’s European full-category online retail brand designed to bring customers a faster, more convenient, and cost-effective shopping experience. Offering same-day and next-day delivery across the UK, Joybuy combines speed, reliability, and affordability to meet the needs of modern shoppers. In this role, you will enhance and optimise the customer journey, address pain points in the customer experience, and transform complex data into actionable insights that fuel business growth. You will work closely with engineering, data science, marketing, commercial, and operations teams to deliver user-centric solutions in a dynamic, international environment. \n \n Key Responsibilities: \n\n • Identify and enhance opportunities within the mobile apps user journey, including features like new customer acquisitions, search, recommendations, promotions, product details, guided shopping, payment options and customer reviews.\n, • Define customer lifecycle and segments, establish performance metrics, and create a structured approach to product performance.\n, • Manage product roadmaps and launch milestones, integrating customer insights, industry trends, and data analytics to optimise user experience.\n, • Work with cross-functional teams to shape and implement app product strategies based on user needs and business plans that extend to our global markets.\n, • Empower Business Initiatives and facilitate decision making from both a user-centric perspective and machine learning capability.\n\n \n Minimum Qualifications: \n\n • Recent 5+ years of experience in product management (mobile apps and web apps) in creating / mapping customer user journey experience from end to end in the e-commerce industry for European countries.\n, • Bachelor’s degree in Computer Science, Business Administration, Product Management, Finance, Engineering, or a related field.\n, • Strong analytical and communication skills to effectively collaborate across various teams and leverage data for decision-making.\n, • Bilingual level language proficiency in English and at least one of the following, Dutch, German or French.\n\n \n Preferred Qualifications: \n\n • Proven track record of large user base apps (e.g. managing app products with over 1 million daily active users).\n, • Experience working across different regions and diverse cultures is advantageous.\n\n \n What We Offer: \n\n • A dynamic and challenging work environment in a leading global e-commerce company.\n, • The opportunity to work with a diverse international team and to make a significant impact on JD.com's global presence.\n, • Competitive salary and benefits package, including health insurance, retirement plans, and performance bonuses.\n\n \n JD.com is committed to creating a diverse environment and is proud to be an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, or veteran status.

\n Data Science Leader \n AI for Science, Research Intelligence & Knowledge Discovery \n Technology – Data Science Organization \n \n Are you ready to lead the teams building AI that helps advance science? \n Are you motivated to shape AI and data science strategy that drives meaningful impact across products, customers, and business outcomes? \n Would you enjoy leading teams to build advanced AI systems that power knowledge discovery and innovation at scale? \n \n About our Team \n Our global team support products education electronic health records that introduce students to digital charting and prepare them to document care in today’s modern clinical environment. We have a very stable product that we’ve worked to get to and strive to maintain. Our team values trust, respect, collaboration, agility, and quality. \n \n About the Role \n In this role, you will define and lead AI and data science strategy across machine learning, NLP, search, and generative AI to deliver impactful, scalable solutions. You will guide teams through the full lifecycle of AI systems, from experimentation to production, while aligning work to product goals and customer needs. You will also influence senior stakeholders, shape roadmaps, and drive measurable outcomes across the organisation. \n \n Responsibilities \n\n • Set AI and data science strategy across ML, NLP, search, recommendation, experimentation, and generative AI, aligning work to product goals, customer needs, and business priorities.\n, • Lead and develop high-performing teams by coaching talent, setting priorities, fostering scientific rigor, and building an inclusive, collaborative culture.\n, • Deliver advanced AI and knowledge-discovery systems across the full lifecycle, from experimentation through production, including LLMs, RAG, search, and domain-enriched AI solutions.\n, • Drive evaluation and AI quality by establishing robust frameworks, metrics, experimentation practices, and responsible AI standards.\n, • Influence across product, technology, and business by partnering with cross-functional leaders, shaping roadmaps, translating technical insights, and aligning teams on customer and business impact.\n\n \n Requirements \n\n • Significant experience in data science, AI/ML, NLP, information retrieval, statistics, or a related quantitative field, or equivalent practical experience.\n, • Excellent technical expertise across modern data science methods, including machine learning, experimentation, deep learning, generative AI, and production AI systems.\n, • Hands-on experience delivering AI-powered products, including LLMs, RAG, semantic search, embeddings, agentic workflows, and knowledge-driven systems.\n, • Proven success leading and developing technical teams in complex product, platform, or research environments.\n, • Experience working with large, complex datasets and building scalable, maintainable, production-ready AI/ML systems.\n, • Exceptional people leadership, prioritization, communication, and stakeholder management skills, with the ability to turn ambiguity into clear strategy and measurable outcomes.\n\n \n Work in a Way That Works for You \n We promote a healthy work/life balance across the organisation. We offer an appealing working prospect for our people. With numerous wellbeing initiatives, shared parental leave, study assistance, and sabbaticals, we will help you meet your immediate responsibilities and your long-term goals. \n \n Working Pattern \n Working flexible hours - flexing the times when you work in the day to help you fit everything in and work when you are the most productive \n \n About the Business \n A global leader in information and analytics, we help researchers and healthcare professionals advance science and improve health outcomes for the benefit of society. Building on our publishing heritage, we combine quality information and vast data sets with analytics to support visionary science and research, health education and interactive learning, as well as exceptional healthcare and clinical practice. At Elsevier, your work contributes to the world's grand challenges and a more sustainable future. We harness innovative technologies to support science and healthcare to partner for a better world. \n \n Together, we create possibilities. Join us.

Quantitative Researchers at Xantium are responsible for researching and developing mathematical models used to identify investment and trading opportunities in the global financial markets. \n \n The process is collaborative, involving direct access to and guidance from senior quantitative portfolio managers and engineers with years of experience across all major markets. Our Quantitative Researchers learn a range of skills including various research techniques, how to work with different types of data, markets and asset classes. \n \n Examples of responsibilities include: \n \n\n • Analyzing and evaluating financial and alternative datasets\n, • Researching existing and developing new techniques in machine learning\n, • Researching, developing and implementing quantitative trading signals/models\n, • Developing and maintaining modeling infrastructure\n, • Supporting production trading operations\n\n \n Quantitative Researcher applicants should have a PhD (or equivalent) that involved intense mathematics or statistics. We may consider candidates without PhDs, provided they can demonstrate strong competitive math backgrounds and strong academic records.

Hybrid working pattern (3/2) \n \n An opportunity has arisen for a Risk Analyst to join a leading global energy trading organisation based in London. \n \n This role since within the analytics team which constantly strives to improve risk procedures through automation, therefore a significant aspect of the role would be to contribute to the development of software to streamline daily processes and assist front office with system trading, using a variety of techniques including machine learning and artificial intelligence. \n \n Alongside the automation elements, you will also be responsible for the daily analysis of the trading activities (PnL and position reporting) of the gas desk, as well as providing ad hoc support to other desks as required, notably Crude Oil Derivatives, LNG, and Power & Emissions. \n \n Main Responsibilities: \n \n\n • Preparing and reviewing daily P&L and risk reports, monitoring limits, and proactively resolving any issues in coordination with the relevant teams.\n, • Support front office in obtaining approval for new and non-standard products.\n, • Assisting in identifying significant risks within the business and ensuring they are transparent to senior management.\n, • Provide information and commentary for the bi-weekly Risk Committee meetings.\n, • Review and approve any relevant changes to the main ETRM system (Endur).\n, • Guarantee compliance for trading procedures with relevant controls and support when necessary internal and external audit requests.\n, • Participate in the enhancement of reporting and the development of reporting systems.\n\n \n Skills and Experience Required: \n \n\n • University degree in a numerate discipline (e.g. economics, mathematics, pure science, finance, engineering or similar).\n, • c.2 years’ experience in a similar Analyst / Risk role within commodity trading companies, ideally with a focus on gas & power.\n, • Strong knowledge of risk metrics such as VaR, stress-testing, scenario analysis.\n, • Good knowledge of derivatives and options.\n, • Strong knowledge of MS Office suite including Excel and VBA. SQL and Python would be a strong advantage.\n, • Knowledge of the Endur ETRM system would be an advantage.\n, • Strong organization skills with good attention to detail and the ability to work to tight deadlines.\n, • Strong communication skills, able to communicate concisely with senior management in the market risk function and with all stakeholders.\n, • Fluent level of English.\n

We are working with a leading healthcare AI pioneer transforming drug development through cutting-edge artificial intelligence and world-leading multi-modal generative AI foundation models. \n \n The Opportunity \n We're seeking an exceptional Software / Machine Learning Engineer to join their central London office, working on novel Foundation Models. This is a rare opportunity to work at the intersection of advanced software engineering and frontier AI research, building systems that directly enable breakthroughs in drug development and patient care. \n \n Your work will directly accelerate research velocity, enabling the team to iterate faster, experiment more effectively, and push the boundaries of what's possible in AI-driven healthcare. \n \n Role Requirements \n \n Core \n\n • Strong general software engineering skills: clean, tested Python, comfortable owning systems end to end\n, • Hands-on experience with large, messy datasets - cleaning, joining, versioning, and validating data at scale\n, • Experience making ML training and inference run efficiently on very large data: caching, data loading, memory management, cross-node communication\n, • Working knowledge of PyTorch and/or JAX training loops\n, • Experience running workloads on HPC or multi-node GPU clusters (e.g. Slurm, distributed training)\n\n \n Bonus points \n\n • Prior work with health records, single-cell / cytometry data, or time-series\n, • Prior experience working with Tabular data / datasets\n, • Comfortable across the stack — data pipelines, model training, and evaluation — rather than specialising in one\n, • Experience in a startup or small, fast-moving research team; ships without heavy process\n\n \n Nice to haves \n\n • A biology or clinical background, or a demonstrated interest in learning the domain\n, • Familiarity with secure data environments (NHS TREs, data governance, de-identification)\n\n \n Why This Role is Different \n\n • Impact: Your work will directly accelerate research that's transforming drug development and saving lives. The tools you build will enable breakthroughs in understanding and treating complex diseases.\n, • Technical Challenge: Work on genuinely novel problems at the frontier of ML engineering. You'll tackle challenges around scale, complexity, and domain-specific constraints that few engineers ever encounter.\n, • Cutting-Edge Research: Collaborate daily with world-class researchers pushing the boundaries of AI in healthcare. You'll be exposed to the latest developments in foundation models, multi-modal learning, and medical AI.\n, • Autonomy & Ownership: Take ownership of critical systems and make architectural decisions that shape the technical direction. Your input will directly influence research capabilities and velocity.\n, • Fast-Paced Growth: Join during a period of rapid scaling with opportunities to grow your skills, take on increasing responsibility, and help shape the engineering culture.\n\n \n Location & Work Environment \n This role is approx 4 days a week based in their London office, where the majority of the technical team, including ML researchers and engineering teams, are located. You'll be at the heart of R&D activities, with daily opportunities for face-to-face collaboration, whiteboard sessions, and rapid iteration with the team. \n \n They foster a culture of intellectual curiosity, technical rigor, and collaborative problem-solving. The environment balances the urgency and pace of a fast-growing startup with the thoughtfulness and precision required for building foundation AI models that must meet the highest standards of accuracy and reliability.

Senior Data Scientist \n \n Location – London – Hybrid \n \n Salary - £70k – £82,5k + Benefits \n \n Please Note: Due to the AWESOME nature of this work, Applicants must hold a valid British \n passport - Duel Nationality wont be accepted - sorry \n \n Some data science roles are about optimising marketing campaigns or improving recommendation engines, this isn't one of them. \n \n We're looking for an experienced Data Scientist to work on highly secure, technically demanding projects where the questions are complex, the data is challenging and the outcomes genuinely matter. You'll work alongside experts from a range of disciplines, using machine learning, AI and advanced analytics to solve problems that have real-world impact. \n \n You'll be trusted to explore, experiment and develop practical solutions where there isn't always a predefined answer. \n \n What you'll be doing \n \n You'll lead the design and delivery of advanced data science solutions, combining analytical thinking with strong engineering principles to build models that can be relied upon in production. \n Your work could involve: \n \n\n • Developing machine learning models that solve complex operational challenges.\n, • Working with structured, unstructured and streaming data to uncover meaningful insights.\n, • Designing scalable data pipelines and production-ready AI solutions.\n, • Collaborating directly with technical and non-technical stakeholders to shape the right approach.\n, • Evaluating emerging AI techniques and applying them where they deliver genuine value.\n, • Building robust, maintainable Python solutions using modern engineering practices.\n, • Helping shape technical direction while mentoring others and sharing knowledge across the team.\n\n \n What we're looking for - We're far more interested in how you think than simply the tools you've used. \n \n You'll likely have: \n \n\n • At least five years' commercial experience delivering data science or machine learning solutions.\n, • A strong academic background in a STEM discipline.\n, • Excellent Python skills and experience developing production-quality machine learning solutions.\n, • Experience working with cloud platforms such as AWS, Azure or Google Cloud.\n, • Knowledge of modern software engineering practices, CI/CD and version control.\n, • Experience working with SQL and/or NoSQL technologies.\n, • The confidence to explain technical concepts clearly to a wide range of audiences.\n, • A genuine curiosity for solving difficult problems and continuously learning.\n\n \n \n Interested? Then let’s talk!

Data Analyst / Scientist or Senior Data Analyst / Scientist \n Bristol or London \n \n About us \n \n Hoare Lea is a human-centric and planet-conscious engineering consultancy. We offer intelligent and sustainable solutions to complex design challenges for the built environment throughout the UK and further afield. \n \n We provide a wide range of engineering and consultancy services, including acoustics, air quality, building services (MEP), fire, lighting, security and sustainability to name but a few. Together, our highly skilled teams use technical expertise and problem-solving skills to bring buildings to life. We ensure that whatever the building, its design is outstanding, and its operations meet the needs of the communities it serves. \n \n We are as committed to providing an environment where everyone can realise their unique potential. So, in joining Hoare Lea, you will experience a business that enriches your knowledge, supports your wellbeing, and welcomes your individuality. You’ll have the opportunity to participate in our 9-day fortnight scheme, thriving community groups, varied social and networking events, and extensive professional and technical development schemes. We also offer an extensive benefits package, including private medical cover, an electric vehicle salary sacrifice scheme, stock options, and 25 days of annual leave (increasing with service), alongside flexible and hybrid working. \n \n Whatever your ambitions or circumstances, our aim is to enable everyone to develop their knowledge, give their best, and enjoy what they do. \n \n About the role \n \n Our multi-disciplinary software, product, and data team serves as a central hub of digital expertise and innovation, supporting projects across the company. We work collaboratively with engineers, consultants and other specialists to use data and technology to solve real-world problems and improve the services we provide to our clients. \n \n We have an opportunity for a Data Analyst/Scientist or Senior Data Analyst/Scientist to play a key role in using data, analytics, statistical methods and data science to generate insight, support decision-making and improve our engineering services. \n \n This is a broad analytical role. You will work across the full lifecycle of a problem: understanding stakeholder needs, exploring and assessing data, identifying appropriate analytical approaches, communicating findings and, where appropriate, developing statistical or machine-learning models or client-ready insights/tools. This is a role for someone who enjoys variety and has a critical eye for finding the right solution for the problem. Sometimes this may be exploratory analysis, a dashboard or a set of clearly defined metrics; in other cases, it may involve forecasting, statistical modelling, machine learning or building/working with AI. \n \n It's an exciting time to join our Digital team. Working alongside a range of specialist engineers and consultants, you will be joining a collaborative, knowledgeable, highly engaged team, and offer a supportive, flexible, and high-performing work culture. In a time where building and energy resilience is ever more important, we are driving forward innovation to make an impact with data and technology. \n \n You will have the opportunity to engage in a variety of high-impact projects, working on challenging problems for some of the UK’s most notable organisations, including the NHS and Oxford University. Our team has recently worked on creating data science-led for managing estates in hospitals, building energy forecasting models, and harnessing data on building performance to create better designed buildings of the future. \n \n In this key and varied role, you can expect to: \n \n\n • Work with engineers, consultants, product teams and other stakeholders to understand their needs and translate sometimes ambiguous questions into well-defined analytical problems.\n, • Develop and implement data-driven solutions to solve real-world business problems across the company.\n, • Use SQL, Python and other analytical tools to investigate datasets, identify trends and relationships, test hypotheses and generate actionable insights.\n, • Apply appropriate statistical techniques, forecasting methods, ML and AI approaches where they add value to the problem being solved.\n, • Collaborate with the product and software engineering teams to turn analytical work into reusable tools, workflows and data-driven products where appropriate.\n, • Develop reproducible and maintainable analytical code, following best practices, including version control, testing, and peer reviews.\n, • Contribute to the development of analytical and data science capability across the business by sharing approaches, reusable methods and good practice\n\n \n About you \n \n To be successful in this role you’ll need: \n \n Essential skills: \n \n\n • Experience applying data and analysis to real-world business, engineering or operational problems.\n, • Strong analytical problem-solving skills, with the ability to take an initially ambiguous question and determine an appropriate analytical approach.\n, • Ability to work on projects independently and own deliverables.\n, • Strong proficiency in Python for data manipulation, analysis, visualisation and data science (e.g., Pandas, NumPy, Scikit-learn).\n, • Proficiency in data querying languages (e.g., SQL). Solid understanding of software engineering best practices (version control, unit testing, code review, etc.).\n, • Strong experience with data visualisation frameworks (e.g., PowerBI, Streamlit).\n, • Experience applying machine learning and AI, including generative AI, to real-world problems where it provides clear benefit.\n, • Familiarity with statistical concepts and their application in data analysis.\n, • Solid communication skills, capable of effectively engaging with and presenting findings to both technical and non-technical audiences.\n, • Understanding of data governance, privacy, responsible AI and other relevant standards.\n\n \n Desirable skills: \n \n\n • Knowledge of the engineering industry and its challenges.\n, • Experience with one of the major machine learning frameworks (TensorFlow or PyTorch).\n, • Knowledge of mathematical optimisation methods, such as linear, integer or constraint optimisation, and associated tools (e.g. OR-Tools).\n, • Experience with MS Fabric or equivalent data warehousing solution.\n, • Experience working in a cloud computing environment.\n, • Familiarity with containerisation and deployment technologies (e.g., Docker, CI/CD pipelines).\n\n \n For candidates joining at Senior level, we would additionally expect you to lead more complex or ambiguous analytical projects, shape analytical approaches and overarching priorities, work independently with senior stakeholders, review and support the work of others, and help raise analytical standards across the team. \n \n How to apply \n \n To apply simply complete a CV profile and submit your application. \n \n If shortlisted, one of our recruitment team will be in touch to arrange an introductory call (about 30 minutes) to discuss the role and your experience in more detail. From there, successful candidates will be invited to attend a panel interview, either via Microsoft Teams or in person at one of our offices. We aim to provide feedback at each stage of the process. \n \n Adjustments and accommodations \n \n If there are adjustments or accommodations that we can put in place to help you participate and give your best at any stage of the recruitment process (whether relating to disability, neurodivergence or anything else) please let us know. \n \n Data privacy \n \n We have updated our terms and conditions for candidates, click here to find out more. \n \n Recruitment agencies \n \n We have a Preferred Supplier List of trusted partners who assist us when required. We do not acknowledge speculative CVs or unsolicited candidate introductions from agencies not on the list. \n

Member of Technical Staff - AI Infrastructure / ML Platform \n Location | London (Hybrid) \n Comp | Highly Competitive + Meaningful Equity \n Focus | AI Infrastructure, MLOps, Data Platform, GPU Systems, Research Infrastructure, Scientific ML \n \n We’re partnering with a stealth AI4Science company building foundational technology designed to accelerate science. \n \n Backed by significant funding and leading technology investors, the company is bringing together exceptional researchers, engineers and scientists to tackle problems where advances in AI can translate into discoveries in the physical world. \n \n Unlike traditional software environments, the infrastructure here sits directly underneath a scientific research engine: large-scale model training and inference, simulation, experimental data, GPU workloads and research workflows all need to work together reliably. \n \n They are now looking for a Member of Technical Staff focused on AI Infrastructure / ML Platform to help build that foundation. \n \n This is an early and highly influential hire. You’ll work directly with researchers and scientists, understand how they actually experiment, and build the systems that allow them to move significantly faster. \n \n About The Role \n As a Member of Technical Staff, you’ll own infrastructure across the intersection of ML systems, data, compute and research engineering. \n \n The challenge isn’t to build an enormous internal platform for its own sake. It’s to understand what researchers need, identify the bottlenecks slowing them down, and build the smallest, strongest abstractions that make experimentation faster and more reliable. \n \n You could be working on GPU orchestration one week, research data infrastructure the next, and improving model serving, experiment reproducibility or distributed training workflows after that. \n \n You’ll have significant freedom to make build-vs-buy decisions, introduce new infrastructure where it creates genuine leverage, and deliberately avoid unnecessary complexity where it doesn’t. \n \n Examples Of The Problems You Might Tackle \n\n • Building the ML platform researchers use to train, evaluate, deploy and iterate on scientific models.\n, • Designing infrastructure for GPU-intensive training and inference workloads, including scheduling, resource utilisation and workload isolation.\n, • Improving distributed model serving using technologies such as vLLM, TensorRT, Triton, Ray or equivalent systems.\n, • Building reliable data pipelines and storage systems connecting simulation, modelling, experimental data and downstream research workflows.\n, • Creating reproducible experimentation environments so researchers can move quickly without repeatedly solving infrastructure problems.\n, • Designing systems for experiment tracking, model versioning, evaluation, observability and lineage.\n, • Improving inference latency, throughput, GPU utilisation and cost efficiency.\n, • Building internal APIs, tooling and abstractions that make complex infrastructure accessible to researchers without constraining how they work.\n, • Supporting workloads that may move between local compute, cloud infrastructure and dedicated GPU environments.\n, • Designing systems capable of evolving as the organisation moves from individual research experiments towards increasingly automated scientific workflows.\n\n \n What You’ll Do \n\n • Build the research platform: Design the infrastructure connecting models, compute, data and scientific workflows, allowing researchers to move from an idea to a reproducible experiment quickly.\n, • Own AI infrastructure: Build and operate GPU infrastructure for model training and inference, thinking carefully about scheduling, utilisation, latency, throughput, reliability and cost.\n, • Build the data layer: Develop scalable pipelines and systems for ingesting, processing, storing and serving scientific, simulation and experimental data.\n, • Productionise research: Help researchers move promising ideas beyond notebooks into robust systems without introducing unnecessary process or infrastructure overhead.\n, • Improve model serving: Profile and optimise inference workloads, choosing the right serving architecture and hardware configuration for different models and research requirements.\n, • Design for researchers: Work directly with Research Scientists and Engineers to understand how they work and build tools that increase their velocity rather than forcing them into rigid platform abstractions.\n, • Make pragmatic architecture decisions: Start from requirements, scale and constraints before choosing technologies. Decide what should be built internally, what should be borrowed and what simply doesn’t need to exist yet.\n, • Shape the technical foundation: As an early infrastructure hire, you’ll have significant influence over architecture, engineering standards and how the research platform develops as the company scales.\n\n \n What We’re Looking For \n\n • Strong software engineering fundamentals and excellent coding ability, particularly in Python.\n, • Experience building ML infrastructure, ML platforms, MLOps or distributed systems in production.\n, • Strong understanding of the lifecycle around modern machine learning systems — data, training, evaluation, deployment, inference and monitoring.\n, • Experience working with GPU workloads and an understanding of the performance and reliability challenges surrounding them.\n, • Experience with containerisation and orchestration technologies such as Docker and Kubernetes.\n, • Strong understanding of cloud infrastructure and Infrastructure-as-Code.\n, • Experience designing reliable data pipelines, APIs and distributed services.\n, • Ability to reason from first principles about requirements, scale, constraints and trade-offs, rather than defaulting to technologies you’ve previously used.\n, • Comfortable working closely with researchers and translating loosely defined scientific requirements into robust engineering systems.\n, • Ability to independently own technically difficult problems in a highly ambiguous environment.\n\n \n You’ll Likely Thrive Here If \n\n • You enjoy building infrastructure from first principles rather than inheriting a mature platform with every abstraction already defined.\n, • You care about making researchers dramatically more productive.\n, • You can move comfortably between ML systems, data engineering, cloud infrastructure and software engineering.\n, • You understand that good infrastructure is often about what you choose not to build.\n, • You naturally think about GPU utilisation, latency, throughput, reliability, observability and cost.\n, • You enjoy profiling systems and finding where the real bottleneck sits.\n, • You’re comfortable supporting different models, frameworks and research workflows rather than designing around one narrow use case.\n, • You want your infrastructure work to enable scientific discovery and physical-world outcomes, rather than another consumer or enterprise software product.\n, • You enjoy small, highly technical teams where individual engineers have substantial ownership.\n\n \n Nice To Have \n\n • Experience with vLLM, TensorRT-LLM, Triton, Ray / KubeRay or similar ML-serving infrastructure.\n, • Experience designing distributed GPU training or inference systems.\n, • Experience with PyTorch, JAX or other scientific/deep-learning frameworks.\n, • Experience with large-scale data ingestion and research-data platforms.\n, • Experience building self-service ML platforms or tooling for Research Scientists.\n, • Experience with model registries, experiment tracking, lineage, evaluation and reproducibility.\n, • Strong Kubernetes, Terraform and cloud infrastructure experience.\n, • Experience optimising inference through batching, caching, quantisation, scheduling or hardware-aware optimisation.\n, • Experience in AI4Science, scientific computing, HPC, frontier AI or research-heavy engineering environments.\n, • Interest in the intersection of AI, science and automated experimentation.\n\n \n What’s On Offer \n\n • Highly competitive compensation + meaningful equity\n, • Join a well-funded, early-stage AI4Science company at a foundational point in its journey.\n, • Significant ownership over the infrastructure underpinning the research organisation.\n, • Work alongside exceptional AI researchers, engineers and scientists.\n, • Build systems spanning frontier ML, scientific data, simulation and experimentation.\n, • Opportunity to influence architecture and engineering culture from an early stage.\n, • Work where improvements to infrastructure directly increase the speed at which scientists can experiment, learn and discover.\n, • London-based, collaborative environment with flexibility around hybrid working.\n\n \n If you’re interested in learning more, feel free to reach out | danny@salientgroup.com.au \n

The Role \n \n Front Office AI Strategy & Implementation Specialist – Boutique Hedge Fund \n \n Martis Search are delighted to be partnering with a successful and highly entrepreneurial Hedge Fund on what we believe is one of the most innovative and forward-looking opportunities currently available within the Hedge Fund market. \n \n We are representing a boutique, London-based diversified Hedge Fund in the appointment of a permanent “Front Office AI Strategy & Implementation Specialist.” \n \n This is a newly created, highly strategic hire and represents the firm’s first dedicated AI-focused appointment. The role offers exceptional visibility across the organisation and the opportunity to work directly alongside Portfolio Managers, Investment Analysts and senior leadership to help shape how AI is embedded into the investment process. \n \n In summary, this is a predominantly Front Office-facing role focused on leveraging AI technologies to improve investment decision-making, optimise workflows, enhance research capability and ultimately contribute towards revenue generation and alpha creation across the business. \n \n The successful candidate will report directly to the COO (with the potential for the role to evolve into a dedicated Front Office reporting line over time) and will act as the central point of expertise for AI implementation across the firm. \n The position combines investment knowledge, technical capability and stakeholder engagement, requiring an individual who can bridge the gap between investment professionals and AI-enabled solutions. \n \n The role will involve: \n \n\n • Identifying and implementing practical AI use cases across investment and operational functions.\n, • Working closely with Portfolio Managers and Investment Analysts to enhance research, idea generation and decision-making processes.\n, • Helping shape the firm’s broader AI strategy and long-term roadmap.\n, • Promoting the responsible, secure and effective use of AI technologies across the organisation.\n, • Building, testing and deploying AI-driven tools and workflows.\n, • Acting as an internal advisor and educator to support adoption across the business.\n\n \n Our client currently utilises the Enterprise versions of both Anthropic Claude and OpenAI ChatGPT. Therefore, demonstrable experience using AI tools within a Fixed Income and/ or Credit investment environment is considered essential. \n \n The firm is open-minded regarding background and recognises that strong candidates may come from a variety of Front Office or technical investment disciplines. However, applicants should ideally possess a minimum of 5-years’ experience within Fixed Income and/or Credit markets. \n \n Examples of relevant backgrounds may include: \n \n\n • Fixed Income/ Credit Quantitative Analyst\n, • Fixed Income/ Credit Quantitative Developer\n, • Fixed Income/ Credit Data Engineer/ Machine Learning SME\n, • Fixed Income/ Credit Research Analyst\n, • Fixed Income/ Credit Portfolio Manager\n, • Investment Technology, or Front Office Strategy Specialist within a Hedge Fund, or Asset Management environment\n\n \n Candidates must possess outstanding academic credentials from a leading university, alongside exceptional communication and stakeholder management skills. The successful individual will regularly engage with senior investment professionals and will be expected to operate in both an advisory and hands-on delivery capacity. \n \n The role is 4-days per week in the office and x 1 day working-from-home. \n \n Key Responsibilities \n \n\n • Partner with Front Office teams and senior management to identify opportunities where AI can improve productivity, research capability and investment decision-making.\n, • Run workshops, demonstrations and one-to-one sessions to encourage AI adoption and innovation across the business.\n, • Design and implement AI-enabled tools, workflows and solutions.\n, • Contribute towards the development of the firm’s AI governance and best-practice framework.\n, • Document, maintain and oversee AI tools and related processes.\n, • Act as a key internal advocate for the practical and responsible use of AI technologies.\n\n \n Key Requirements \n \n\n • Strong understanding of Fixed Income and/ or Credit products and investment processes.\n, • Hands-on exposure to AI, machine learning, data engineering or workflow automation.\n, • Strong analytical, numerical and problem-solving capabilities.\n, • Experience building or working with custom GPTs, AI assistants, connectors or AI-enabled workflows.\n, • Strong appreciation of both the opportunities and limitations associated with AI technologies.\n, • Excellent interpersonal and communication skills, with the ability to engage both technical and non-technical stakeholders.\n, • Ability to operate in a fast-paced, entrepreneurial environment and manage multiple initiatives simultaneously.\n, • Systems-oriented mindset with the ability to conceptualise processes, workflows and scalable solutions.\n\n \n Preferred Technology Exposure \n \n\n • OpenAI ChatGPT Enterprise\n, • Anthropic Claude Enterprise\n, • Python\n, • JavaScript\n, • VBA\n, • Power BI\n, • Excel\n, • AI workflow automation and data visualisation tools\n\n \n Additional Desirable Experience \n \n\n • CFA and/or IMC qualification advantageous.\n, • Experience within Hedge Funds, Asset Management, or institutional investment environments preferred.\n\n \n The firm is highly flexible regarding background, seniority and overall profile, with the primary focus being on identifying an individual capable of driving meaningful change and innovation across the organisation. \n \n This is a rare opportunity to join a growing Hedge Fund in a genuinely strategic capacity and play a defining role in how AI is integrated into the investment process from an early stage. \n \n Salary \n \n Between £200,000 k pa - £500,000 k pa dependent upon experience, plus competitive bonus, pension, healthcare etc.

Senior Applied AI Engineer \n London | Hybrid – 2 days per week onsite | £110,000–£140,000 + Equity \n We’re working with an exciting high-growth AI business that is building technology to transform how organisations research, assess and manage risk. \n The company has developed a sophisticated AI-driven platform that combines LLMs, unstructured data and intelligent automation to deliver high-quality insights in a high-stakes environment. With significant growth and increasing demand internationally, they’re now looking for a Senior Applied AI Engineer to help take their AI systems to the next level. \n This is a genuinely hands-on engineering role for someone who enjoys taking AI from prototype through to reliable production systems. \n The Role \n You’ll work closely with the Head of Research and Product teams, building and improving production LLM systems that deliver accurate, valuable outcomes for real users. \n You’ll be responsible for: \n\n • Building and improving production LLM-driven systems, including RAG and agentic workflows.\n, • Developing high-quality, reliable and well-tested Python code.\n, • Designing and implementing evaluations (evals) that genuinely measure whether AI systems are improving.\n, • Investigating and resolving real-world production failures and understanding their root causes.\n, • Improving the accuracy, cost and latency of AI systems.\n, • Working closely with Product to shape and deliver new AI capabilities.\n, • Architecting and maintaining scalable microservice-based systems.\n, • Experimenting with LLMs, prompting and related technologies to solve complex problems.\n, • Supporting and mentoring more junior engineers.\n, • Working in an environment where AI coding tools and agentic development are heavily embedded into the engineering workflow.\n\n What We're Looking For \n We're looking for a strong software engineer who has moved deeply into Applied AI rather than someone coming purely from an academic or research background. \n You'll ideally have: \n\n • 4+ years' experience building production software.\n, • 2+ years' experience building production LLM applications.\n, • Strong hands-on experience with Python.\n, • Experience building RAG systems, LLM applications and/or AI agents.\n, • A strong understanding of how LLM systems work, including areas such as embeddings, prompting and model parameters.\n, • Experience designing AI evaluations and measuring the quality of LLM outputs.\n, • A strong understanding of software engineering principles, testing and production reliability.\n, • Experience working in a fast-moving environment, ideally within a startup or scale-up.\n, • Excellent communication skills and the ability to explain technical concepts clearly.\n, • A product-focused mindset and the ability to make sensible engineering decisions in ambiguous environments.\n\n Desirable Experience \n It would be advantageous if you also have experience with: \n\n • LLM fine-tuning\n, • Agentic AI systems\n, • Microservice architecture\n, • Go\n, • Deep learning / traditional machine learning\n, • AI coding and agentic development tools such as Claude Code, Codex or similar\n\n What This Role Isn't \n This isn't an academic research position and you won't be expected to train foundation models. \n We're particularly interested in engineers who have actually shipped AI products into production and understand the challenges that come with reliability, accuracy, cost, latency and real users. \n You should be comfortable getting stuck into problems, experimenting quickly, understanding when an AI system isn't performing as expected and then engineering a solution. \n Why Join? \n\n • £110,000–£140,000 salary\n, • Equity package\n, • Hybrid working – 2 days per week in London\n, • Opportunity to work on genuinely challenging Applied AI problems\n, • Significant influence over the development of the company's AI platform\n, • Work closely with senior technical and product leadership\n, • £1,000 annual professional development budget\n, • Private healthcare\n, • Life insurance\n, • Unlimited holiday\n\n The business has already secured significant investment and is experiencing strong international growth, making this an exciting time to join and have a genuine impact on the direction of the technology.

Project Manager – AI Delivery \n Outside IR35 \n 3 days a week on site \n Initial contract until the end of the year \n \n Must have hands on experience working on different AI initiatives \n \n We’re looking for an experienced Project Manager – AI Delivery to lead the end-to-end delivery of exciting AI, Generative AI and intelligent automation initiatives within a regulated banking environment. \n \n Sitting within the Transformation & Change function, you’ll work across Product, Data, Engineering, Architecture, Risk, Compliance, Information Security and Operations to take AI solutions from initial concept through to successful production deployment. \n \n What you’ll be doing \n \n You’ll be responsible for delivering a range of AI-enabled transformation initiatives, which could include Generative AI, internal AI assistants, customer-facing conversational AI, intelligent document processing, workflow automation, knowledge-management solutions and machine-learning capabilities. \n \n Key responsibilities will include: \n \n\n • Leading AI and automation projects from initial business case and planning through design, build, testing, implementation and post-launch review.\n, • Managing project plans, budgets, resources, milestones, risks, issues and dependencies.\n, • Coordinating multidisciplinary teams across AI/Data, Engineering, Product, Architecture, Operations and third-party suppliers.\n, • Managing senior stakeholders and providing clear reporting through steering committees, programme boards and governance forums.\n, • Ensuring AI solutions meet appropriate regulatory, security, data privacy, model risk and Responsible AI requirements.\n, • Supporting release and go-live activities, including operational readiness, change approvals, deployment and transition into BAU.\n, • Driving user adoption, benefits realisation and measurable business outcomes.\n, • Managing external AI technology partners, SaaS providers and other third-party suppliers.\n\n \n What we’re looking for: \n \n You’ll be an experienced Technology Project Manager with a strong track record of delivering complex technology change, ideally within banking or regulated financial services. \n \n You should have: \n \n\n • Experience delivering AI, Machine Learning, intelligent automation or advanced analytics initiatives.\n, • Strong end-to-end technology project delivery experience.\n, • Experience working within regulated financial services environments.\n, • Experience managing cross-functional teams including AI/Data specialists, engineers and business stakeholders.\n, • Experience delivering cloud-hosted technology solutions.\n, • Strong knowledge of technology governance, risk management and the software delivery lifecycle.\n, • Experience managing vendors and SaaS/technology partners.\n, • Excellent stakeholder management and communication skills, including working with senior stakeholders.\n, • The ability to operate effectively in an environment with ambiguity, experimentation and competing priorities.\n\n \n This is a great opportunity for a strong technology Project Manager who understands AI delivery and can successfully balance innovation, pace, governance and regulatory requirements to bring AI solutions into production.

Job Title: Audit Data Analytics Manager \n Office: Flexible to be based at any of our office locations (Hybrid) \n Competitive salary, negotiable depending on your experience and expertise. \n \n Are you ready to bring your Audit Data Analytics expertise to a role where your skills and unique perspective can make a lasting impact? \n \n What Sets Us Apart \n At MHA, we’re about people first – our people, our clients, and the communities we serve. As one of the UK’s top 11 accountancy firms and a proud member of Baker Tilly International, the 9th largest network in the world, we are a hub of global knowledge with a strong local commitment. \n Our people-focused approach truly sets us apart. Here, you won’t just be another face in the firm; you’ll be part of an ambitious, driven team dedicated to continuous learning and growth. We invest in our people because they are the foundation of our success. With access to unparalleled resources and award-winning development programmes, you’ll have the freedom to shape your career while making a meaningful impact. We take immense pride in being awarded gold for Investors in People. This recognition reflects our deep commitment to nurturing talent and ensuring every individual feels valued and supported. \n \n Here, You’ll Go Beyond Numbers \n We’re looking for a talented Audit Data Analytics Senior Manager who thrives in a dynamic environment and embraces the chance to tackle complex challenges. At MHA, you’ll be surrounded by passionate professionals who are dedicated to making a difference. Your work in Audit will go beyond the numbers – it’s about building meaningful client relationships, understanding their businesses, navigating risks, and delivering insights that drive real results. \n \n Manages the day-to-day operations of the ADA team, leads complex engagement support, oversees AI and GenAI development initiatives, and takes primary responsibility for ADA governance, compliance and quality frameworks. \n \n\n • Delivers hands-on data analytics expertise and solutions to engagement teams, enabling more effective and efficient audits\n, • Builds data analytics capabilities across the entire audit practice through structured learning programmes, resources and continuous skills development.\n, • Embeds data analytics techniques into standard audit methodology to ensure consistent application, regulatory compliance and quality outcomes.\n, • Research, designs and implements AI solutions that addresses non-judgemental audit procedures and routines.\n, • Creates and maintains bespoke data analytics tools and workflows that enhance audit quality, improve efficiency and address firm-specific requirements.\n, • Drives the identification, assessment and implementation of emerging technologies and approaches to transform audit quality and differentiate the firm's service offering.\n, • Establishes and maintains the frameworks, controls and processes that ensure data analytics work meets professional standards and regulatory expectations.\n\n \n What We’re Looking For \n\n • Fully qualified ACA/ACCA with a minimum of 2-3 years’ post qualified experience in a technical role, external audit or equivalent.\n, • Relevant recent experience with audit data analytics software and an awareness of current developments.\n, • Proficiency in low-code development platforms\n, • Expert-level skills in Power BI or similar data visualization tools\n, • Strong understanding of audit processes and methodologies\n, • Excellent problem-solving and analytical skills\n, • Ability to communicate complex technical concepts to non-technical audiences\n, • Demonstrable ability to work well within a team and on your own.\n, • Influencing – the ability to persuade others of your point of view.\n, • Knowledge of machine learning and AI applications in audit\n\n \n Rewards That Resonate \n You’re more than a number to us; you’re an individual with unique talents and aspirations. Our benefits are designed to support your well-being, foster your professional growth, and recognise your contributions. \n\n • Agile Working: Enjoy the flexibility of core hours from 10 AM to 2 PM and two home working days, allowing you to balance your work and personal commitments seamlessly.\n, • 25 days holiday Plus Bank Holidays, plus the opportunity to buy or sell up to 5 days\n, • Competitive salary package\n, • Employee recognition awards: Outstanding Performance Award Bonus and other recognition initiatives.\n, • New and improved programme for succession planning and supportive management structure to help you realise your potential\n, • Employee Assistance Programme: Access a free confidential 24-hour support service, including unlimited counselling sessions and virtual doctors available for you and your family.\n, • And lots more!\n\n \n Are You Ready to Elevate Your Career? \n Apply now and be part of a team that celebrates diversity, champions innovation, and prioritises your success! \n

\n The Head of Institutional Credit Management (ICM) is a critical Managing Director (C16) level executive role reporting directly to the Chief Client Officer, who is a member of Citi's Executive Management Team. This pivotal leadership position is responsible for competitively positioning Citi by driving the development, execution, and continuous optimisation of an end-to-end wholesale credit underwriting and management platform. The incumbent will serve as an execution-oriented leader, ensuring that the highest quality control standards for wholesale credit analysis and portfolio monitoring are consistently met across the enterprise. By establishing and monitoring critical production and control metrics, the Head of ICM will drive credit and portfolio actions, and safeguard the firm's capital while enabling business growth. Organisational Context and Mission Operating within Citi's Client Organisation, Institutional Credit Management consists of a global workforce of approximately 3,000 professionals. The Client Organisation is dedicated to empowering client growth through a deep, anticipatory understanding of client needs, using the full breadth of Citi's global product capabilities. Within this framework, ICM serves as a best-in-class, first-line-of-defence (in-business) organisation. The mission of ICM is to deliver a seamless, end-to-end wholesale credit management platform in close, collaborative partnership with Citi's lines of business, independent risk management, and key corporate functions. This ensures a unified, firmwide approach to client strategy, segmentation, and coverage, delivering consistent, high-quality services in all geographies. Strategic Leadership and Transformation As a global leader, the Head of ICM must possess a sophisticated global perspective and a strategic mindset capable of translating future market possibilities into breakthrough organisational strategies. The role demands the ability to lead large-scale, cross-border teams, taking a holistic and broad view when addressing systemic issues. The incumbent will drive growth and lead transformation by anticipating future shifts in financial markets, navigating evolving regulatory landscapes with agility, and guiding the organisation through rapid technological advancements. This includes nurturing a culture of adaptability and continuous innovation, actively identifying future skill gaps, and providing robust reskilling opportunities to ensure the workforce remains competitive and future ready. A key aspect of this leadership will involve effectively managing a large team, fostering a high-performance culture, and ensuring alignment with the strategic objectives and growth aspirations of Citi's wholesale businesses. Stakeholder Management and Collaboration Effective stakeholder management and deep collaboration are central to the success of this role. The Head of ICM is also responsible for managing interactions with external stakeholders, including government bodies, regulatory agencies, and clients. Internally, the incumbent must build strong partnerships and interact regularly on complex credit and risk issues with the Board of Directors, the Chief Executive Officer, the Executive Management Team (EMT), and cross-franchise leaders. By instilling trust through honesty, integrity, and authenticity, the Head of ICM will balance the competing needs of multiple stakeholders, lead senior-level client relationships, and negotiations, and foster significant cross-business and cross-functional alignment to meet shared corporate objectives. Risk Management, Regulatory Compliance and Crisis Response A primary responsibility of the Head of ICM is the rigorous management of credit risk and the adherence to firm policies and regulatory standards. The incumbent will be personally responsible for addressing, managing, and successfully discharging material regulatory requirements. This requires maintaining a high level of constructive engagement with global regulators and demonstrating a proven ability to collaborate effectively with internal control functions, such as Internal Audit and Fundamental Credit Risk (FCR), as well as external auditors. Furthermore, the Head of ICM must possess deep event and crisis management expertise to guide the organisation through complex geopolitical events, business continuity disruptions, cybersecurity threats, and data privacy challenges, ensuring operational resilience under pressure. The Head of ICM will also work closely with the second line of defence Risk function to ensure all operations are in accordance with wholesale credit policies, thereby driving consistency and robustness in the credit management framework. Functional Expertise, Technology and Credit Workflow Systems Effectively tolead a modern credit management platform, the Head of ICM must possess excellent technology skills and a deep, practical understanding of credit workflow systems. The role requires a sophisticated grasp of evolving technology trends, including the integration of real-time data feeds for dynamic risk monitoring and the implementation of predictive modeling for risk forecasting. Under the incumbent's leadership, ICM will drive innovation in credit management processes and systems, offering credit capabilities powered by artificial intelligence and machine learning. By collaborating with business and technology partners to implement solutions, using advanced analytics for predictive credit insights, and enhancing cybersecurity measures, the Head of ICM will capitalise on opportunities for disruptive change to maintain Citi's competitive advantage. Furthermore, a critical focus will be on driving operational efficiencies and achieving operational leverage, ensuring the ICM platform can effectively support increasing business volumes and evolving wholesale lending activities. The ideal candidate will be a highly effective and distinguished business leader with a minimum of 15 years of risk or risk-related credit work experience within major global banking or financial institutions. This extensive background must reflect deep knowledge of wholesale credit portfolios, credit workflow systems, and a proven track of executing monitoring strategies and priorities across diverse lines of business and geographies. The candidate must demonstrate strong ethics, unwavering integrity, and the courage to address difficult issues transparently and in a timely manner. Exceptional decision-making capabilities under pressure and tight timelines are essential, complemented by outstanding verbal and written communication skills and the ability to deliver compelling presentations to senior executives, board members, and regulatory authorities. Candidates applying for this role must be aware that it is a Certified Role, subject to the FCA and PRA Certification Regime. The Certification Regime is one element of the Individual Accountability Regime which came into effect on 7 March 2016. Under the Certification Regime, Citi UK regulated entities (Citi entities) must ensure that employees working in certain roles categorised as specified significant harm functions (Certified Roles) are assessed as fit and proper to carry out their role. Under the guidance provided by the FCA and PRA, firms should have regard to the following when assessing fitness and propriety: \n \n • Honesty, integrity and reputation\n, • Financial soundness\n, • Competence and capability\n \n In order to comply with the requirements of the Certification Regime, Citi entities must take reasonable care to ensure that an employee does not perform a Certified Role without first being certified as Fit and Proper. For this reason, you will be assessed for this role against the Fit and Proper requirements, as described above. This assessment will be carried out through extensive interviews, self disclosures, permitted criminal record checks, regulated reference checks, credit checks and other background screening checks. \n Working at Citi is far more than just a job. A career with us means joining a team of approximately 219,000 dedicated people from around the globe. At Citi, you'll have the opportunity to grow your career, give back to your community and make a real impact. \n #J-18808-Ljbffr

\n As a Quantitative Trading & Research - Market Microstructure Researcher in the AI Market Lab, you will frame problems, build measurement and simulation machinery, run careful ablation studies, and develop models/strategies that hold up across venues, regimes, and operational constraints. The ideal candidate has worked close to live trading systems and can translate research insights into execution- and latency-aware designs., \n \n • Analyze high-frequency market data, including Level 2 and, where available, Level 3 or Level 4 order-book and order-event data, to identify predictive structure and trading opportunities.\n, • Develop alpha signals and trading features based on order flow, liquidity, queue dynamics, price formation, cross-venue behavior, and short-horizon market response.\n, • Design, backtest, and implement market-making and risk-taking strategies, including pricing, order placement, cancellation, queue-position management, fill-probability estimation, and inventory control.\n, • Develop realistic research and simulation methodologies incorporating latency, fees, rebates, market impact, adverse selection, and operational constraints.\n, • Optimize strategy performance across signal generation, portfolio or position sizing, execution, and intraday risk management.\n, • Work closely with traders, quantitative developers, technology partners, exchanges, and ECNs to move strategies into production and improve them using live performance and markout analysis\n, • Advanced degree or equivalent practical experience in mathematics, statistics, physics, computer science, engineering, financial engineering, or a related quantitative discipline.\n, • Relevant full-time quantitative research experience in high-frequency / medium-frequency trading, electronic market making, or systematic execution.\n, • Strong understanding of electronic market mechanics: order types, matching engines, queue priority, microstructure invariants, liquidity formation, and market impact/adverse selection.\n, • Evidence of contributing to strategies used in live markets, including a clear understanding of the research-to-production workflow and the sources of performance degradation in deployment.\n, • Strong programming and data-analysis skills in Python; proficiency in C++ or another high-performance language is highly desirable.\n, • Demonstrated rigor in experimental design and evaluation-ability to separate economically meaningful effects from overfitting, leakage, optimistic fills, and regime-specific artifacts.\n Preferred Qualifications, Capabilities, and Skills\n \n, • Experience independently owning a strategy, managing a trading book, or leading a quantitative research workstream.\n, • Deep expertise in one or more areas: high-frequency market making, short-horizon alpha, execution research, multi-venue routing/optimization, or microstructure modeling.\n, • Experience across FICC markets or multiple asset classes; outstanding equities specialists interested in transitioning to FICC are encouraged.\n, • Familiarity with machine learning, deep learning, or reinforcement learning applied to limit-order-book modeling, execution, or control problems.\n, • Research publications, open-source contributions, or substantial internal research artifacts demonstrating a sustained, hypothesis-driven approach.\n \n Join a pioneering team at the forefront of systematic trading innovation. The Quantitative Trading & Research (QTR) group is responsible for systematic trading across FX, Rates, Commodities, Credit, Equity and a wide range of markets. Within QTR, AI Market Lab brings together quantitative research, modern artificial intelligence, market microstructure, and high-performance engineering to develop the next generation of electronic trading capabilities. Our work spans signal research, pricing, market making, execution, portfolio construction, risk management, and the production systems that support them., J.P. Morgan is a global leader in financial services, providing strategic advice and products to the world's most prominent corporations, governments, wealthy individuals and institutional investors. Our first-class business in a first-class way approach to serving clients drives everything we do. We strive to build trusted, long-term partnerships to help our clients achieve their business objectives., J.P. Morgan's Commercial & Investment Bank is a global leader across banking, markets, securities services and payments. Corporations, governments and institutions throughout the world entrust us with their business in more than 100 countries. The Commercial & Investment Bank provides strategic advice, raises capital, manages risk and extends liquidity in markets around the world. \n #J-18808-Ljbffr

Senior Research Engineer \n Cambridge or London, UK (100% Onsite) \n \n Our client is a global leader in semiconductor innovation, developing advanced technologies that power billions of smart devices worldwide. With significant investment in artificial intelligence research, the company is driving the next generation of AI-enabled computing by combining world-class research with real-world engineering. \n \n This is an exciting opportunity for a Research Engineer to join a collaborative team where cutting-edge ideas become practical solutions. As a Research Engineer, you'll work on advanced machine learning technologies including large language models, reinforcement learning, optimisation, and generative AI, helping shape future semiconductor design and AI systems. \n \n If you're a Research Engineer looking to bridge research and implementation while working alongside leading AI experts, this is an opportunity to make a genuine impact. \n \n Key Responsibilities \n\n • Implement and evaluate novel machine learning algorithms and AI research concepts.\n, • Develop prototypes and proof-of-concept systems to support research initiatives.\n, • Collaborate with researchers to translate theoretical ideas into practical software solutions.\n, • Build and enhance research infrastructure, experimentation pipelines, and internal tooling.\n, • Analyse experimental results and contribute to technical reports and documentation.\n, • Stay informed of emerging AI research and recommend new approaches where appropriate.\n\n \n Required Experience & Skills \n\n • PhD with at least 2+ years relevant post-doc or research exp.\n, • Published at top ML or NLP conferences such as NeurIPS, ICML, EMNLP, ICCV etc.\n, • Experience with Large Language Models (LLMs), Reinforcement Learning, optimisation techniques, or generative AI.\n, • Experience developing research infrastructure or ML tooling.\n, • Knowledge of distributed training, GPU computing, or CUDA.\n, • Exposure to semiconductor technologies, chip design, or applied AI research.\n, • Commercial or research experience implementing machine learning algorithms.\n, • Strong programming skills in Python; C++ experience is advantageous.\n, • Experience with PyTorch, TensorFlow, JAX, or similar deep learning frameworks.\n\n \n Why Apply? \n\n • Join a world-class AI research team working on cutting-edge machine learning technologies.\n, • Play a key role in applying AI to next-generation semiconductor innovation.\n, • Work alongside experienced researchers and engineers in a highly collaborative environment.\n, • Excellent opportunities for technical development and long-term career progression.\n\n \n Recruiter's Note \n We're looking for candidates who enjoy building real-world AI systems from cutting-edge research rather than purely publishing papers. Candidates with hands-on experience implementing modern deep learning techniques and a passion for solving complex engineering challenges will thrive in this environment. \n \n Apply now or send a copy of your CV, referencing the title and location, and with a short introduction to cw@eu-recruit.com. \n \n By applying to this role you understand that we may collect your personal data and store and process it on our systems. For more information please see our Privacy Notice (https://eu-recruit.com/about-us/privacy-notice/).

Data Science & AI Delivery Lead \n London \n Hybrid – minimum 3 days per week in the local office \n £90,000–£120,000 base + 15–20% target bonus \n \n \n We are looking for an experienced Data Science & AI Delivery Lead to join a major international organisation investing significantly in Data, AI and advanced analytics. \n This is a senior, hands-on technical leadership position for someone who can combine AI/ML engineering expertise with delivery leadership. You’ll act as the deputy to the Head of Data Science & AI Delivery, taking responsibility for the day-to-day execution of AI initiatives and helping a growing team take solutions from concept and proof of value through to scalable production deployments. \n The organisation sees Data and AI as a major strategic capability – using information to make better decisions, identify opportunities earlier, improve operational efficiency and create competitive advantage. \n Importantly, this is not a purely managerial role. You’ll remain close to the technology, working directly with the codebase, reviewing technical designs and architecture, establishing engineering standards and contributing hands-on when required. \n \n You’ll take a leading role in the technical execution and delivery of AI, machine learning and advanced analytics solutions, including: \n\n • Owning the day-to-day running of AI delivery workstreams, ensuring teams remain focused, unblocked and aligned to priorities.\n, • Acting as deputy to the Head of Data Science & AI Delivery and providing leadership continuity across projects and stakeholder forums.\n, • Taking technical delivery accountability from initial concept through development, deployment and production.\n, • Leading AI solution architecture, technical design reviews, implementation approaches and production-readiness assessments.\n, • Establishing engineering standards, reusable frameworks, patterns and best practices for AI delivery.\n, • Providing technical guidance around solution design, model selection and architecture.\n, • Remaining hands-on with Python development, particularly during critical delivery phases and proof-of-concept work.\n, • Reviewing code and technical outputs to maintain high engineering and quality standards.\n, • Designing and delivering Generative AI and LLM solutions, including RAG architectures, prompt engineering, vector search and integration with Azure AI services.\n, • Defining engineering approaches for LLM applications, agentic AI systems, machine learning solutions and AI platforms.\n, • Establishing strong MLOps practices covering model versioning, automated testing, deployment pipelines, monitoring, observability and model lifecycle management.\n, • Ensuring solutions meet appropriate security, governance, scalability, explainability and operational support requirements.\n, • Evaluating emerging AI technologies and determining where they can deliver meaningful business value.\n, • Working closely with architecture, technology, programme and Data Engineering teams to ensure effective end-to-end delivery.\n, • Supporting delivery planning, timelines, cost estimates, cloud/API consumption and resource allocation.\n, • Mentoring Data Scientists and AI Engineers through architecture reviews, code reviews, pair programming and technical coaching.\n, • Helping create a high-performing engineering culture focused on collaboration, quality and continuous learning.\n\n \n You’ll need demonstrable experience delivering AI and machine learning solutions into production within a professional environment, alongside the technical credibility to lead experienced Data Scientists and AI Engineers. \n Key experience includes: \n\n • Expert-level Python development.\n, • Strong experience with core data science and machine learning libraries such as scikit-learn, pandas, PyTorch and/or TensorFlow.\n, • Practical experience with Databricks, including MLflow and Spark-based data processing.\n, • Hands-on knowledge of Generative AI and LLMs, including prompt engineering, RAG architectures and vector search.\n, • Strong understanding of MLOps, including CI/CD, model testing, deployment, monitoring and model lifecycle management.\n, • Cloud experience, ideally within the Microsoft Azure ecosystem.\n, • Experience with services such as Azure OpenAI, Azure Machine Learning and/or Azure AI Search.\n, • Experience leading technical delivery teams while remaining actively involved in engineering and delivery.\n, • Strong understanding of software engineering practices including Git, code review, documentation and the transition from experimentation to production-grade code.\n, • Excellent stakeholder communication skills, including the ability to translate complex technical concepts into clear business language.\n, • Strong delivery and project management capabilities, including resource estimation, progress tracking and managing competing priorities.\n\n \n We’re particularly interested in people who combine technical depth with leadership ability – someone comfortable discussing strategy with senior stakeholders one moment and reviewing Python code or AI architecture with engineers the next. \n

Role: Senior Project Manager \n Location: London, Tavistock Square \n Hybrid: 3 days in the office \n Salary: £70,000 - £80,000 + Bonus + PMI \n \n As MICHELIN Connected Fleet, a division of the Michelin Group, leader in sustainable mobility for 130 years, we specialise in connected fleet management services and solutions. We are a market leader with over 30 years expertise in a high-growth, competitive mobility technology industry. Today we serve 70,000 customers and over 600,000 vehicles globally, growing more than 10% per year, and entering at the rate of 3 new markets a year. Our AI (artificial intelligence) technology and ML (machine learning) algorithms ensure all fleet data delivers tangible benefits to our customers. Our insights transform operational efficiency, reducing costs, ensuring the safety of drivers and goods while reducing environmental impact, paving the way to predictive fleet management. Backed by Michelin Group and operating under the Michelin Connected Fleet name, we will be a major player in this market in the coming years. \n \n OUR DREAM \n We know our planet is at risk and we urgently need to find innovative ways to protect it. At Michelin, pioneering is what we do: We are innovating constantly, to explore new opportunities, with, around and beyond tires to lead the way in sustainable mobility. Our people act for change, with respect, and as leaders. We care about giving people a better way forward. Our dream is rooted in a single purpose: by 2050, Michelin will be recognised as a critical innovation leader that helped humanity conquer new frontiers. And we all work hard every day to realise this dream. \n \n OUR PEOPLE & WAYS OF WORKING \n At MICHELIN Connected Fleet, agility is not a word - it’s a lifestyle. We gather entrepreneurial minds who are not afraid to fail fast and learn quickly, every day. We think long term and act short term, we grow fast and love what we do. We believe in an inclusive working environment, building teams with a variety of backgrounds, skills, views and opinions. Among our 400 employees in Europe, we proudly benefit from around 30 nationalities. We thrive because of the diverse background and talent of our people. We nurture our team's growth with several company wide development programs - including our Diversity, Mentoring and Sustainability programs. \n \n THE ROLE IN SHORT \n The Senior Project Manager – EU Scale & Product Certification is a critical role within Michelin Connected Fleet’s transformation journey. \n The role exists to stabilise and industrialise our product landscape, ensuring that historical gaps in certification, homologation and regulatory readiness do not constrain future growth. Acting as the single European reference point for compliance and certifications, this role enables scale across the EU, RSA and Australia, while new product introductions are driven in parallel. \n You will operate at the crossroads of Product, Quality, Operations, Legal and Marketing, with high exposure to senior leadership and strong expectations around clarity, ownership and execution. \n \n WHAT WILL I BE DOING: \n \n EU Scale & Regulatory Readiness \n \n\n • Take full accountability for securing and maintaining all required homologations and certifications to enable scale across the EU, RSA and Australia\n, • Build a clear, prioritised remediation plan for legacy product compliance gaps, ensuring risks are identified, documented, owned and resolved\n, • Define and maintain a forward‑looking regulatory roadmap across the 12 countries in which Michelin Connected Fleet operates\n\n \n Quality & Cross‑Functional Coordination \n \n\n • Act as the primary entry point for Customer Experience & Services (CxS) Quality, ensuring issues are correctly analysed, prioritised and addressed\n, • Work closely with Quality leadership and key stakeholders to connect quality signals with product and regulatory actions and ensure that those gets considered for Product roadmap\n, • Coordinate deliverables across CxS Enablers, MCF EAA Operations and Product teams, ensuring dependencies are managed and timelines respected\n\n \n Product Evolution & Risk Management \n \n\n • Translate upcoming regulatory requirements into clear, actionable product evolution requirements\n, • Ensure product decisions balance speed, compliance, scalability and risk\n, • Provide regular, structured updates to senior leadership on progress, risks, and mitigation plans\n\n \n TO BE SUCCESSFUL YOU WILL LIKELY HAVE: \n \n\n • Extensive experience in regulated technology or industrial environments (mobility, automotive, telematics, IoT or similar)\n, • Strong track record managing product certification, homologation or regulatory compliance across multiple countries\n, • Proven ability to operate confidently across Product, Quality, Operations, Legal and Commercial teams\n, • High credibility with senior stakeholders and comfort influencing without formal authority\n, • Structured, resilient and pragmatic approach to legacy complexity and risk\n, • Excellent communication skills, able to simplify complex issues for executive audiences\n\n \n \n Work-life balance is important to us at Michelin Connected Fleet, so we offer our teams as much flexibility as possible in line with the needs of their role. We trust our teams to know how they work best, combining remote and collaborative working, with a flexible approach to hours. This allows our people the time and space for life outside of work.

Principal Recruitment Consultant – Cloud, Data & AI Harrison Clarke | The Search & Venture Firm in Cloud, Data & AI \n \n About Harrison Clarke \n Founded in 2017, we partner with Tier 1 VC-backed startups and high-growth technology companies to build world-class engineering teams. Our mission is simple: align exceptional engineers with groundbreaking businesses that are shaping the future. \n \n We operate across Cloud (DevOps, SRE, Platform Engineering, DevSecOps, Performance Engineering) and Data & AI (Machine Learning, MLOps, Data Engineering, AI Research, and related domains). Through our portfolio of innovative startups and our corporate venture arm (Harrison Clarke Ventures), we give our consultants unique access to some of the most exciting technical hiring opportunities in the market. \n \n The Role \n We are hiring a Principal Recruitment Consultant to work directly with our portfolio of Tier 1 VC-backed startups, owning technical hiring mandates across Cloud, Data and AI. \n This is a senior, high-impact individual contributor role for an experienced recruiter who thrives on building deep relationships with founders, engineering leaders and elite technical talent. You will lead complex, high-stakes searches and help our clients scale the teams that power their products and platforms. \n \n Key Responsibilities \n\n • Own end-to-end recruitment for technical roles across Cloud, Data and AI for a portfolio of Tier 1 VC-backed startups and high-growth companies\n, • Partner closely with founders, CTOs, VPs of Engineering and hiring managers to deeply understand technical requirements, culture and growth plans\n, • Source, engage and assess elite engineering talent (permanent and contingent) using a consultative, relationship-driven approach\n, • Manage the full search lifecycle: briefing, market mapping, candidate development, interviewing coordination, offer negotiation and onboarding support\n\n \n What We’re Looking For \n\n • Proven track record as a successful recruitment consultant with experience placing technical talent into startups or technology companies\n, • Strong domain knowledge or demonstrable interest in Cloud, Data, AI, DevOps/SRE, Platform Engineering, Machine Learning or related fields\n, • Excellent stakeholder management skills, comfortable engaging at founder and senior engineering leadership level\n, • Entrepreneurial attitude with a genuine desire to make an impact in a specialist, high-performance environment\n\n \n What We Offer \n\n • Opportunity to work exclusively with Tier 1 VC-backed startups and innovative companies at the cutting edge of Cloud, Data & AI\n, • Clear career progression pathway with structured development\n, • Competitive base salary + uncapped commission structure\n, • Access to Harrison Clarke Ventures for high achievers\n, • A high-performance culture built on continuous learning, ownership and genuine collaboration\n

We are seeking a Global E-Commerce's Governance and Experience (GNE) is a global team responsible for ensuring a safe and trustworthy marketplace for not only our buyers, but also our sellers and creators . The Moderation Team is part of the GNE organization. Our mission is to create the most trustworthy E-commerce platform with a delightful service experience . We are looking for Moderation Quality Assurance Specialist role to analyse moderation quality performance, evaluating the delivery quality of BPO sites, provide indepth RCA for critical issues as well as the implementation of effective action plans . \n \n Key Responsibilities: \n\n • Content Review & Analysis\n, • Conduct comprehensive review and analysis of sellers, products, content and Intellectual Property Rights (IPR) to ensure compliance with platform policies\n, • Perform daily quality assessments of moderation decisions across multiple content categories\n, • Identify patterns and trends in content violations through systematic data analysis\n, • Review and evaluate the accuracy of content moderation decisions made by BPO teams or machine moderation\n, • Quality Assurance & Process Improvement\n, • Help build quality assessment processes and conduct quality assessment work by ensuring and evaluating the delivery quality of the sellers, products, IPR, and contents reviewed\n, • Participate in the development of quality inspection standards and continuously optimise the processes and platform\n, • Conduct root cause data analysis and provide insights and key actions to improve processes\n, • Develop and implement quality metrics and KPIs to measure moderation effectiveness\n, • Policy Enhancement & Compliance\n, • Enhance moderation policy and work closely with local operations and policy teams\n, • Provide recommendations for policy updates based on content review findings\n, • Ensure adherence to regional regulatory requirements and platform standards\n, • Stakeholder Management & Reporting\n, • Prepare detailed quality reports and analysis for management review\n, • Collaborate with cross-functional teams\n, • Conduct calibration sessions with BPO teams to ensure consistent application of moderation policies\n, • Root Cause Analysis & Action Planning\n, • Perform in-depth RCA (Root Cause Analysis) for critical moderation issues and provide detailed insights on quality gaps\n, • Develop and implement effective action plans to address identified quality issues\n, • Track and monitor the effectiveness of implemented corrective actions\n, • Create case studies and learning materials based on quality analysis findings\n\n \n Qualifications: \n Education & Experience \n\n • Bachelor's degree or above\n, • Minimum 3 years of hands on and in-depth experience in e-commerce safety and quality analysis is a must\n, • Proven experience in content moderation, quality assurance, or trust and safety operations\n, • Experience working with BPO teams preferred\n, • Language & Communication Skills\n, • Fluency in English is a must. Knowledge in another European languages is a plus.\n, • Excellent coordination skills and communication skills across multiple cross-functional teams to build plans and projects\n, • Strong written and verbal communication skills for reporting and stakeholder management\n, • Technical & Analytical Skills\n, • Ability to digest large data sets/policies in a cohesive and actionable manner\n, • Familiarity with office software such as Excel, Word, Power point, etc.\n, • Strong analytical skills with experience in data analysis and reporting\n, • Basic understanding of SQL or data visualization tools is a plus\n\n \n Atain (previously known as IGT Solutions) provides equal employment opportunities to all individuals based on job related qualifications and ability to perform a job, without regard to age, gender, gender identity, sexual orientation, race, color, religion, creed, national origin, disability, genetic information, veteran status, citizenship or marital status, and to maintain a non-discriminatory environment free from intimidation, harassment or bias based upon these groups. \n

With over 20 Million Jobs LinkedIn hosts the largest global talent marketplace. LinkedIn collects, normalizes and indexes job postings from over 50,000 web sources. The Quality Job Growth Product Manager will work closely with a cross functional team of Engineering, Data Science, Product Operations, Business Development, and Product Marketing to grow and improve quality job posts globally.\n \n \nFrom supporting job partnerships with governments around the world to applying Machine Learning to improve our job source quality - this role is highly visible and rich with learning opportunities. This challenging role will provide passionate and data driven individuals the opportunity to positively impact job seekers on a global scale.\n \n Responsibilities \n\n • Understand and lead analyses of user needs, product metrics, and the broader professional landscape to determine the right set of solutions to build to help our members and customers be productive and successful\n, • Drive global product requirements definition, product planning and product design (including writing PRDs) of new features and enhancements\n, • Work collaboratively across teams to deliver on the LinkedIn vision of economic opportunity for every member of the global workforce\n, • Understand how to build an ecosystem product and make trade off decisions for the good of the ecosystemResearch and analyze the broader job market ecosystem\n, • Set ambitious and measurable OKRs and be transparent on executionClearly communicate product benefits to our users and internal stakeholders \nRequired Qualifications \n\n • BS/BA degree in a technology related field OR equivalent experience\n, • 4+ years of experience in product management\n, • Strong analytical skills\n, • Fundamental understanding of API’s and web integration technologies \nPreferred Qualifications \n\n • MS degree in a technology-related field\n, • Experience building and delivering successful SaaS or social network platform solutions\n, • Expertise with applicant tracking systems and/or online job boards\n, • Experience in operating with partner ecosystems in collaboration with business development\n, • Ability to manage and lead across highly cross-functional teams\n, • Ability to communicate findings clearly to both technical and non-technical audiences\n, • Multilingual capabilities would be a benefit in the role, but not a requirement. \n

\n Principal Engineer - Lead Tech Strategy for a Profitable FinTech Scale-Up Hybrid (London) or remote within the UK \n Up to £160,000 per annum plus stock options\n Python | Django | FastAPI | AWS | Rust | Postgres | Event-Driven Architecture | Machine Learning \n Principal Engineer - We're working with a leading fintech scale-up that's transforming how small businesses access finance. Backed by a strong track record and an ambitious mission, they're now looking for a Principal Engineer to lead the next phase of innovation within one of their most critical product areas. \n This is a strategic leadership role offering exceptional autonomy and influence. You'll head up the evolution of a high-impact platform responsible for generating personalised credit offers - a core driver of the business's growth and customer experience. The Opportunity\n As Principal Engineer, you'll take ownership of the technical strategy and architecture for dynamic, data-driven systems that determine the financial products offered to new customers. This is a unique chance to define the future of adaptive credit systems, driving smarter, faster and more relevant lending decisions using real-time data and experimentation. \n The Principal Engineer will work closely with senior leadership across engineering, data, product and design. You'll also mentor engineers, steer long-term vision and ensure delivery aligns with key business outcomes. What Makes This Role Stand Out?\n \n • Strategic Impact: You'll lead the architectural vision and execution of systems at the heart of a high-growth fintech.\n, • Technical Ownership: Full responsibility for evolving and scaling a domain-critical platform.\n, • Cross-Functional Collaboration: Partner with experienced teams across disciplines to shape solutions from the ground up.\n, • Mission-Driven Environment: Work for a business that's empowering small businesses and making finance more accessible.\n What We're Looking For:\n \n, • Strong experience in systems architecture and software development (object-oriented languages).\n, • Proven ability to deliver large-scale technical projects in fast-paced environments.\n, • A business-oriented mindset: you can translate complex problems into scalable, value-driven solutions.\n, • A collaborative leader who has mentored teams and influenced product direction.\n, • Experience working with complex domain models and evolving codebases.\n \n Bonus skills include: Python, Django, PostgreSQL, event-driven data systems, machine learning familiarity and frontend awareness. \n Burns Sheehan Ltd will consider applications based only on skills and ability and will not discriminate on any grounds. \n #J-18808-Ljbffr

\n Director/Senior Director, Strategic Solutions – Industrial Defense and/or Ministry of Defense (Public Sector)\n London, Greater London, England, United Kingdom · Sales \n C3 AI (NYSE: AI), is the Enterprise AI application software company. C3 AI delivers a family of fully integrated products including the C3 Agentic AI Platform, an end-to-end platform for developing, deploying, and operating enterprise AI applications, C3 AI applications, a portfolio of industry-specific SaaS enterprise AI applications that enable the digital transformation of organizations globally, and C3 Generative AI, a suite of domain-specific generative AI offerings for the enterprise.Learn more at: C3 AI \n C3 AI is hiring Directors/Senior Directors, Strategic Solutions. This is a quota carrying sales role which will allow you to further develop your career with a rapidly growing leader in Enterprise AI software. \n The ideal candidate will come with a well-established network of relationships they can immediately leverage to drive meetings and momentum from day one. Prior experience selling into the military, Ministry of Defence and/or law enforcement is essential. Military professionals and individuals with deep domain understanding of national security missions are strongly encouraged to apply. \n You will target and work with organisations within the defence sector to develop high-value AI use cases and AI application roadmaps. You will help defence customers achieve their digital transformation objectives through identifying high-value opportunities. \n We are looking for motivated individuals with a hard work ethic and track record of achievement. You will receive a highly competitive salary and excellent benefits along with generous commissions and equity. In addition to strategic sales training, you will be supported by senior management and mentors to help ensure your success. \n Candidates should be able to understand complex issues at the intersection of mission, operations, business and technology, and communicate that complexity with clarity. Successful candidates will thrive in a fast-paced, high- performance, highly collaborative environment and demonstrate an ability to execute precisely and quickly. Candidates should possess technical fluency in AI, machine learning, operations research, physics, math, engineering, data integration, or computer science. \n Responsibilities: \n \n • Develop and execute a comprehensive sales strategy to drive revenue growth within the defence sector, targeting key individuals within defence organisations and departments.\n, • Identify and prioritise key accounts, cultivating relationships with senior-level decision-makers, program managers, and influencers within defence organisations.\n, • Understand the unique challenges, requirements, and procurement processes of the defence sector, and tailor sales approaches and solutions accordingly.\n, • Engage in strategic relationships with defence customers to assure the realisation of their digital transformation goals.\n, • Develop, maintain, and manage the implementation of strategic defence customer engagement plans.\n, • Manage efforts to research and identify customer prospects and targets.\n, • Collaborate with sales, engineering, products, and marketing teams to develop new product offerings within existing and new lines of business.\n, • Represent C3 AI by driving business development with company alliance partners.\n, • Personally engage in strategic account selling, business development, and ongoing customer success.\n, • Travel to customer sites up to 50% of the time (or more) depending on business needs.\n \n Qualifications: \n \n • Proven track record of success in sales with a focus on selling SaaS solutions to the defence sector.\n, • Deep understanding of the defence industry landscape, procurement processes, and acquisition programmes.\n, • Extensive knowledge of AI technology, data analytics, and their applications within the defense sector.\n, • Demonstrated experience in building and nurturing relationships with senior-level decision-makers and influencers within defence organisations.\n, • Degree in engineering, science, computer science, or related technical field of study. Master’s or MBA degree preferred.\n, • Experience with and understanding of AI and Machine Learning is highly favorable.\n, • Exemplary written and oral communication skills.\n, • Excellent interpersonal, planning, and organisational skills.\n, • Strong analytical skills.\n, • Sales consulting or management consulting experience preferred.\n \n C3 AI provides excellent benefits, a competitive compensation package and generous equity plan. \n #J-18808-Ljbffr

The ideal candidate's favorite words are learning, data, scale, and agility. You will leverage your strong collaboration skills and ability to extract valuable insights from highly complex data sets to ask the right questions and find the right answers. \n \n Required Skills and Qualifications \n \n\n • Strong commercial experience in Python development for data science and machine learning applications.\n, • Proven experience working with Generative AI models, including Large Language Models (LLMs) and AI-powered solutions.\n, • Knowledge and hands-on experience with cloud platforms, preferably AWS and/or Microsoft Azure.\n, • At least 1 - 2 years' of experience in quantitative analytics or data modeling\n, • Deep understanding of predictive modeling, machine-learning, clustering and classification techniques, and algorithms\n, • Fluency in a programming language (Python, C,C++, Java, SQL)\n, • Familiarity with Big Data frameworks and visualization tools (Cassandra, Hadoop, Spark, Tableau)\n\n \n Desirable Skills & Experience \n\n • Familiarity with MLOps, AI governance, and responsible AI practices.\n, • Experience with modern AI frameworks and tooling such as LangChain, Hugging Face, OpenAI, Bedrock, Azure AI Services, or similar technologies.\n, • Knowledge of containerization and deployment technologies such as Docker and Kubernetes.\n\n \n \n

SaaS Data Analyst / Product Owner \n \n Remote / Home-based | Occasional London travel \n \n We’re looking for a SaaS Data Analyst / Product Owner to join an ambitious B2B SaaS business developing innovative products for the property and financial services sectors. \n This is a hands-on role where you’ll sit at the intersection of data, product, customers and technology. You’ll work closely with leadership, customers and developers to turn business needs into well-designed, data-driven products, with a particular focus on AI and automation. \n \n What you’ll be doing \n\n • Own and manage product backlogs, priorities and delivery\n, • Translate high-level requirements into clear functional, screen and data designs\n, • Analyse data and processes to identify opportunities for AI and automation\n, • Develop and refine algorithms and data-driven solutions\n, • Work closely with developers using an agile Scrumban approach\n, • Lead UAT, releases and delivery milestones\n, • Engage with customers and internal stakeholders to understand needs and communicate solutions\n, • Support product launches, documentation and live product issues\n\n \n What we’re looking for \n You’ll have experience in a Data Analyst, Data Scientist, Functional Designer or Product Owner role, ideally within a B2B SaaS environment. \n \n You should have: \n\n • Strong SQL and relational database skills\n, • Experience with data analysis and basic statistics\n, • The ability to understand JSON and data manipulation\n, • Excellent written, analytical and communication skills\n, • Experience creating functional specifications and product designs\n, • A pragmatic, problem-solving approach and strong attention to detail\n, • Confidence working with both technical teams and customers\n, • An interest in AI, machine learning and emerging technology\n\n \n You’ll be a self-starter who enjoys working collaboratively in a fast-paced environment and wants to play a key role in shaping and delivering new SaaS products. \n \n

We are seeking a Global E-Commerce's Governance and Experience (GNE) is a global team responsible for ensuring a safe and trustworthy marketplace for not only our buyers, but also our sellers and creators . The Moderation Team is part of the GNE organization. Our mission is to create the most trustworthy E-commerce platform with a delightful service experience . We are looking for Moderation Quality Assurance Specialist role to analyse moderation quality performance, evaluating the delivery quality of BPO sites, provide indepth RCA for critical issues as well as the implementation of effective action plans . \n \n Key Responsibilities: \n\n • Content Review & Analysis\n, • Conduct comprehensive review and analysis of sellers, products, content and Intellectual Property Rights (IPR) to ensure compliance with platform policies\n, • Perform daily quality assessments of moderation decisions across multiple content categories\n, • Identify patterns and trends in content violations through systematic data analysis\n, • Review and evaluate the accuracy of content moderation decisions made by BPO teams or machine moderation\n, • Quality Assurance & Process Improvement\n, • Help build quality assessment processes and conduct quality assessment work by ensuring and evaluating the delivery quality of the sellers, products, IPR, and contents reviewed\n, • Participate in the development of quality inspection standards and continuously optimise the processes and platform\n, • Conduct root cause data analysis and provide insights and key actions to improve processes\n, • Develop and implement quality metrics and KPIs to measure moderation effectiveness\n, • Policy Enhancement & Compliance\n, • Enhance moderation policy and work closely with local operations and policy teams\n, • Provide recommendations for policy updates based on content review findings\n, • Ensure adherence to regional regulatory requirements and platform standards\n, • Stakeholder Management & Reporting\n, • Prepare detailed quality reports and analysis for management review\n, • Collaborate with cross-functional teams\n, • Conduct calibration sessions with BPO teams to ensure consistent application of moderation policies\n, • Root Cause Analysis & Action Planning\n, • Perform in-depth RCA (Root Cause Analysis) for critical moderation issues and provide detailed insights on quality gaps\n, • Develop and implement effective action plans to address identified quality issues\n, • Track and monitor the effectiveness of implemented corrective actions\n, • Create case studies and learning materials based on quality analysis findings\n\n \n Qualifications: \n Education & Experience \n\n • Bachelor's degree or above\n, • Minimum 3 years of hands on and in-depth experience in e-commerce safety and quality analysis is a must\n, • Proven experience in content moderation, quality assurance, or trust and safety operations\n, • Experience working with BPO teams preferred\n, • Language & Communication Skills\n, • Fluency in English is a must. Knowledge in another European languages is a plus.\n, • Excellent coordination skills and communication skills across multiple cross-functional teams to build plans and projects\n, • Strong written and verbal communication skills for reporting and stakeholder management\n, • Technical & Analytical Skills\n, • Ability to digest large data sets/policies in a cohesive and actionable manner\n, • Familiarity with office software such as Excel, Word, Power point, etc.\n, • Strong analytical skills with experience in data analysis and reporting\n, • Basic understanding of SQL or data visualization tools is a plus\n\n \n Atain (previously known as IGT Solutions) provides equal employment opportunities to all individuals based on job related qualifications and ability to perform a job, without regard to age, gender, gender identity, sexual orientation, race, color, religion, creed, national origin, disability, genetic information, veteran status, citizenship or marital status, and to maintain a non-discriminatory environment free from intimidation, harassment or bias based upon these groups. \n

We are seeking a Global E-Commerce's Governance and Experience (GNE) is a global team responsible for ensuring a safe and trustworthy marketplace for not only our buyers, but also our sellers and creators . The Moderation Team is part of the GNE organization. Our mission is to create the most trustworthy E-commerce platform with a delightful service experience . We are looking for Moderation Quality Assurance Specialist role to analyse moderation quality performance, evaluating the delivery quality of BPO sites, provide indepth RCA for critical issues as well as the implementation of effective action plans . \n \n Key Responsibilities: \n\n • Content Review & Analysis\n, • Conduct comprehensive review and analysis of sellers, products, content and Intellectual Property Rights (IPR) to ensure compliance with platform policies\n, • Perform daily quality assessments of moderation decisions across multiple content categories\n, • Identify patterns and trends in content violations through systematic data analysis\n, • Review and evaluate the accuracy of content moderation decisions made by BPO teams or machine moderation\n, • Quality Assurance & Process Improvement\n, • Help build quality assessment processes and conduct quality assessment work by ensuring and evaluating the delivery quality of the sellers, products, IPR, and contents reviewed\n, • Participate in the development of quality inspection standards and continuously optimise the processes and platform\n, • Conduct root cause data analysis and provide insights and key actions to improve processes\n, • Develop and implement quality metrics and KPIs to measure moderation effectiveness\n, • Policy Enhancement & Compliance\n, • Enhance moderation policy and work closely with local operations and policy teams\n, • Provide recommendations for policy updates based on content review findings\n, • Ensure adherence to regional regulatory requirements and platform standards\n, • Stakeholder Management & Reporting\n, • Prepare detailed quality reports and analysis for management review\n, • Collaborate with cross-functional teams\n, • Conduct calibration sessions with BPO teams to ensure consistent application of moderation policies\n, • Root Cause Analysis & Action Planning\n, • Perform in-depth RCA (Root Cause Analysis) for critical moderation issues and provide detailed insights on quality gaps\n, • Develop and implement effective action plans to address identified quality issues\n, • Track and monitor the effectiveness of implemented corrective actions\n, • Create case studies and learning materials based on quality analysis findings\n\n \n Qualifications: \n Education & Experience \n\n • Bachelor's degree or above\n, • Minimum 3 years of hands on and in-depth experience in e-commerce safety and quality analysis is a must\n, • Proven experience in content moderation, quality assurance, or trust and safety operations\n, • Experience working with BPO teams preferred\n, • Language & Communication Skills\n, • Fluency in English is a must. Knowledge in another European languages is a plus.\n, • Excellent coordination skills and communication skills across multiple cross-functional teams to build plans and projects\n, • Strong written and verbal communication skills for reporting and stakeholder management\n, • Technical & Analytical Skills\n, • Ability to digest large data sets/policies in a cohesive and actionable manner\n, • Familiarity with office software such as Excel, Word, Power point, etc.\n, • Strong analytical skills with experience in data analysis and reporting\n, • Basic understanding of SQL or data visualization tools is a plus\n\n \n Atain (previously known as IGT Solutions) provides equal employment opportunities to all individuals based on job related qualifications and ability to perform a job, without regard to age, gender, gender identity, sexual orientation, race, color, religion, creed, national origin, disability, genetic information, veteran status, citizenship or marital status, and to maintain a non-discriminatory environment free from intimidation, harassment or bias based upon these groups. \n

\n Job Description\n \n AI Research sits within the Chief Data & Analytics Office (CDAO) at JPMorganChase which is responsible for accelerating the firm's data and analytics journey. This includes ensuring the quality, integrity, and security of the firm's data, as well as leveraging this data to generate insights and drive decision-making. The CDAO is also responsible for developing and implementing solutions that support the firm's commercial goals by harnessing artificial intelligence and machine learning technologies to develop new products, improve productivity, and enhance risk management, effectively and responsibly. \n \n As a Vice President / Research Lead in AI Research, you will work on developing novel techniques, tools, and frameworks to model and solve complex large-scale problems in the bank. You will develop a close understanding of the challenges in practical applications of AI and leverage that understanding to formulate new research directions and solutions that can shift the frontier. Your work will span from early-stage innovation and rigorous evaluation to production-scale delivery in close collaboration with engineering and product teams. \n \n Job responsibilities\n \n \n \n • Work on multiple commercially oriented research projects in collaboration with internal data scientists, applied engineering teams and stakeholders across businesses e.g. Commercial & Investment Banking (including Markets), Asset & Wealth Management, Consumer & Community Banking, etc.\n \n • Formulate problems, generate hypotheses, develop new algorithms and models, conduct experiments and rigorous evaluations, synthesize and communicate results, and deliver well-tested, high-quality code.\n \n • Contribute to high-impact business applications, reusable assets and products, and research initiatives.\n \n • Provide thought leadership on internal and external forums through white papers, publications and presentations.\n \n • Lead projects or major workstreams in larger projects/initiatives. Play a key role in ensuring that problem definitions and solutions are technically sound, generalizable and capture business/product requirements.\n \n • Proactively identify and propose new research initiatives motivated by long-term business needs.\n \n \n \n Required qualifications, capabilities, and skills\n \n \n \n • PhD in Computer Science, Engineering, or related fields with relevant research & work experience in AI/ML\n \n • Research publications in top-tier AI/ML venues (e.g., conferences, journals) - broad conferences such as NeurIPS, ICML, ICLR, etc., or highly regarded specialized conferences such as ICAPS, CRYPTO, etc.\n \n • Deep understanding of fundamental AI/ML techniques and a strong grasp of current state of the art in specific areas of expertise.\n \n • Effective verbal and written communication skills with the ability to address both technical and business audiences.\n \n • Practical software development experience in collaborative project settings such as open-source projects or industry experience. Ability to deliver modular, optimized, high-quality Python code with tests.\n \n • Experience leading and mentoring AI researchers, partnering with engineering and business stakeholders to drive execution and strategic planning across near-term deliveries and longer-horizon research initiatives.\n \n • Demonstrated ability to translate research into real-world impact e.g., production-ready solutions, prototypes/pilots, reusable components, reference architectures, or standards.\n \n • Strong track record of research in one of the following areas: (a) Multimodal model/agent security and safety, alignment, guardrails, red teaming, adversarial attacks and defenses, robustness to distribution shifts (b) Foundation model training for structured data modalities (e.g. tabular, graph) (c) Reinforcement Learning, continual learning (parametric/model-based), model post-training and test-time adaptation.\n \n \n \n Preferred qualifications, capabilities, and skills\n \n \n \n • Practical experience with ML libraries (e.g. PyTorch, TensorFlow/Keras, HuggingFace Transformers etc.), agent frameworks (e.g. LangGraph, Google ADK, etc.), common formal verification tools and languages (e.g., Coq/Isabelle/Lean, TLA+, Alloy, Z3, PDDL).\n \n \n \n #AIR_jobs \n \n About Us\n \n J.P. Morgan is a global leader in financial services, providing strategic advice and products to the world's most prominent corporations, governments, wealthy individuals and institutional investors. Our first-class business in a first-class way approach to serving clients drives everything we do. We strive to build trusted, long-term partnerships to help our clients achieve their business objectives. \n \n We recognize that our people are our strength and the diverse talents they bring to our global workforce are directly linked to our success. We are an equal opportunity employer and place a high value on diversity and inclusion at our company. We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law. We also make reasonable accommodations for applicants' and employees' religious practices and beliefs, as well as mental health or physical disability needs. Visit our FAQs for more information about requesting an accommodation. \n \n About the Team\n \n Our Corporate Technology team relies on smart, driven people like you to develop applications and provide tech support for all our corporate functions across our network. Your efforts will touch lives all over the financial spectrum and across all our divisions: Global Finance, Corporate Treasury, Risk Management, Human Resources, Compliance, Legal, and within the Corporate Administrative Office. You'll be part of a team specifically built to meet and exceed our evolving technology needs, as well as our technology controls agenda. \n #J-18808-Ljbffr

Senior Product Manager\n \n Lifted is the people platform for the frontline with a current focus on social care. We help care providers find and keep amazing people, so that everyone in the world can get the care they need from the right person at the right time. We are growing very fast, having grown from a team of 5 to 50 in less than 2 years, and working with 750 companies in the UK. \n \n The opportunity ahead of us is vast. The care market is doubling in the next 10 years and the people process is often still run on paper. It's a global challenge and we are rising to it. We are backed by leading investors Ada Ventures, Fuel Ventures and Form Ventures. \n \n We are looking for a Senior Product Manager to own our ground-breaking AI recruitment assistant for care providers. That covers everything from the moment a candidate applies to the moment they start work: AI voice screening, interview scheduling, pre-employment compliance checks, and onboarding. The product combines voice AI, machine learning and compliance automation. \n \n The technology team runs as two squads. The Hiring Squad owns screening and onboarding. The Visa Squad owns immigration and compliance. \n \n In six weeks in July, the team went from business case to a working voice AI screening agent with a values-based scoring rubric behind it. The first placements were made through that journey in the same month. The product works, it is early, it needs to scale, and parts of it will need course correction based on what we learn. \n What Lifted expects from this role\n \n\n • Own the strategic vision, goals and roadmap of the product across AI screening and onboarding.\n, • Stay close to users. Seek out feedback from carers and providers and be the voice of the customer internally. Build trust with users by acting on their feedback quickly and visibly.\n, • Grow product engagement and customer love.\n, • Work to two horizons. First, take friction out of the current product and move it from MVP to minimum lovable product. Second, move it towards self-serve, because the volume of candidates the business intends to process cannot be handled any other way.\n, • Obsess over goals. Push the product hard while the compliance advantage still exists.\n, • Shape and drive squad rituals: cycle planning, product prioritisation, and product triage for the Hiring Squad.\n, • Document plans and requirements in high-quality Product Requirement Documents.\n, • This is an experienced hire. The bar is someone who has run a product at this stage before and can work autonomously with their squad.\n\n What you will own\n \n\n • The full candidate journey from application to first day at work, treated as one product rather than a set of features.\n, • The voice AI screening agent: adoption, completion rates, screening quality, and the values-based assessment behind the scoring.\n, • Further agentic solutions across the journey. Screening is the second agent in production, after the success of the onboarding agent.\n, • Integration of screening into the core platform, so interview outcomes, notes, and candidate records live in one place.\n, • Pre-employment compliance checks, including identity verification, documents, and references.\n, • Onboarding experience for both the carer and the provider.\n, • Support as a product research surface. Candidate issues are triaged for a fix, not patched one at a time.\nWhat we are looking for\n \n\n • Experienced product manager. Has grown a product from early stage through to scale\n, • Track record of rapid iteration on a live, early-stage product.\n, • Comfortable shipping agentic AI or LLM-based products in production. Understands evaluation and quality measurement, not just prompting.\n, • High levels of ownership.\n, • Leads their own research. Speaks to real users regularly and turns what they hear into actionable insights.\n, • Communicates clearly and manages stakeholder needs. Writes crisp PRDs that engineers can work with.\n, • Driven by data. Pulls and interprets their own numbers, and can explain how the insights are used to drive decision-making.\n, • Passion for our mission, and kindness.\n\n Nice to have\n\n • Recruitment, HR tech, staffing, or marketplace experience is a strong advantage.\n, • UK care sector, or health and social care staffing.\n, • Self-serve and product-led growth experience.\n, • Voice or conversational product experience.\n\n

Senior Data Scientist, London/Oxford hybrid working. \n \n Are you excited by the opportunity to design advanced AI systems that accelerate scientific discovery and unlock knowledge at scale? \n Would you enjoy building production-ready solutions using machine learning, NLP, and generative AI to create meaningful impact for researchers and professionals? \n \n About our Team \n Our global team support products education electronic health records that introduce students to digital charting and prepare them to document care in today’s modern clinical environment. We have a very stable product that we’ve worked to get to and strive to maintain. Our team values trust, respect, collaboration, agility, and quality. \n \n About the Role \n In this role, you will design and deliver advanced AI, NLP, and generative AI solutions that power knowledge discovery and decision support. You will work with complex scientific data and apply modern machine learning and LLM-based approaches to build scalable, reliable systems with real user impact. You will also collaborate across teams to turn complex challenges into practical, production-ready solutions. \n \n Responsibilities \n\n • Design, build, and evaluate advanced AI/ML, NLP, and generative AI solutions for scientific and knowledge-discovery applications.\n, • Develop LLM-powered workflows and retrieval-augmented generation (RAG) systems for search, summarization, question answering, and evidence-grounded insight generation.\n, • Build intelligent retrieval, ranking, recommendation, and decision-support capabilities using modern orchestration frameworks and AI techniques.\n, • Integrate scientific metadata, ontologies, taxonomies, and knowledge assets into scalable AI workflows.\n, • Establish robust evaluation, experimentation, and monitoring frameworks to ensure quality, trust, performance, and reliability.\n, • Write production-ready Python code and partner with engineering teams to deploy solutions at scale.\n, • Provide technical leadership and mentoring to support high-quality delivery and continuous improvement.\n\n \n Requirements \n\n • Practical experience in data science, AI, machine learning, NLP, information retrieval, or a related quantitative field.\n, • Strong hands-on experience building AI/ML, NLP, generative AI, and retrieval-based systems in applied or product-focused environments.\n, • Expertise working with LLMs, including fine-tuning, prompt engineering, grounding strategies, and responsible AI practices.\n, • Strong Python skills and solid machine learning fundamentals.\n, • Experience working with large-scale text or content-rich datasets and modern AI/ML frameworks.\n, • Experience with RAG, semantic, vector, or hybrid search, along with experimentation and evaluation approaches that measure user impact.\n, • Familiarity with cloud platforms and modern software engineering practices.\n, • Strong communication, collaboration, and mentoring skills.\n\n \n Work in a Way That Works for You \n We promote a healthy work/life balance across the organisation. We offer an appealing working prospect for our people. With numerous wellbeing initiatives, shared parental leave, study assistance, and sabbaticals, we will help you meet your immediate responsibilities and your long-term goals. \n \n Working Pattern \n Working flexible hours - flexing the times when you work in the day to help you fit everything in and work when you are the most productive \n \n About the Business \n A global leader in information and analytics, we help researchers and healthcare professionals advance science and improve health outcomes for the benefit of society. Building on our publishing heritage, we combine quality information and vast data sets with analytics to support visionary science and research, health education and interactive learning, as well as exceptional healthcare and clinical practice. At Elsevier, your work contributes to the world's grand challenges and a more sustainable future. We harness innovative technologies to support science and healthcare to partner for a better world.

We're working with a trading pod at a leading global hedge fund looking for an experienced Quantitative Developer to join a systematic equities trading team. \n \n The role sits at the intersection of machine learning, quantitative research and systematic trading, developing and deploying ML models on high-frequency market data and working closely with portfolio management to turn research into live trading signals. \n \n You'll develop and optimise classical and deep learning models, improve distributed computing and large-scale parameter searches, and build efficient workflows from research through to production. \n \n We're looking for someone with 3+ years' experience in software engineering, quantitative development or a similar computational role, with strong Python skills and experience working with large, complex datasets. Experience with distributed computing and Linux is important, while C++ would be a strong advantage. \n \n This is the a unique chance to deploy ML models into systematic trading, and ensure your code and work directly generates profit. \n \n Please apply to find out more.

About our Business: At ICIS, our mission is to optimize the world's resources. We help companies make strategic, sustainable decisions by bringing transparency to markets across the world. We create a comprehensive view of commodities markets, providing companies with the data and intelligence to successfully navigate across global value chains every day. Our customers benefit from instant access to price assessments, reports and forecasts, a dedicated news channel and supply and demand data. You can learn more about ICIS at the link below. https://www.icis.com/explore \n \n About the role: To provide dedicated analytical capability within Customer Intelligence, connecting customer research, CRM data, product usage data and business performance metrics into clear, actionable insight. This role is designed to build future data science and AI capability while strengthening day-to-day reporting, dashboarding and evidence-based decision making. \n You will be responsible for turning customer, commercial and operational data into practical insight that improves customer understanding, product decisions, retention, engagement and business performance. You will work closely with customer researchers and cross-functional partners to bring together quantitative and qualitative evidence, helping the business move towards a more connected view of customer needs, behaviours and outcomes. You will have exposure to data science, automation, AI-ready analytics, cloud environments and customer data architecture. \n \n Responsibilities: \n\n • Analytics and Insight Generation - Analyse customer, product, commercial and operational data to uncover trends, risks and opportunities, delivering insights into customer behaviour, engagement, retention, product adoption and experience. Conduct ad hoc analysis to support strategic initiatives and leadership decisions, while collaborating with Customer Insights teams to combine quantitative data and customer research into actionable recommendations.\n, • Data Management and Reporting - Extract, clean and analyse data using SQL, Python and Excel to support reporting, dashboards and insight packs. Track key customer and business metrics such as NPS, engagement, retention, adoption and usage, while ensuring data is validated, consistent and reliable for decision-making.\n, • Data Science, Automation and AI Readiness - Use Python to automate recurring analysis, reporting and data preparation, while supporting statistical modelling, predictive analytics and AI/data science proof-of-concept work. Identify opportunities to improve insight delivery through automation and emerging analytical methods\n, • Data Visualisation and Storytelling - Create impactful Power BI dashboards and visualisations to communicate customer and business performance, translating complex analysis into clear, actionable insights for technical and non-technical audiences. Support the development of leadership-ready reports, presentations and data-driven recommendations that explain what is happening, why it matters and what actions should follow.\n, • Collaboration and Business Partnership - Collaborate with cross-functional stakeholders to translate business questions into analytical solutions and measurable outcomes. Promote knowledge sharing and a unified view of customer data, while supporting a culture of evidence-based decision-making through the effective use of data and insights.\n\n \n Requirements: \n Essential \n\n • Exceptional analytical and problem-solving skills, with the ability to work with complex datasets and generate practical insight.\n, • Excellent data science and programming skills, with proficiency in Python for data analysis, modelling, automation and statistical applications.\n, • Experience in data manipulation, querying and analysis using SQL.\n, • Skilled in data visualisation and presentation of analytical findings using Power BI.\n, • Competent in Microsoft Excel for data analysis, reporting and business insight generation.\n, • Ability to communicate analytical findings clearly to business stakeholders.\n, • Exceptional attention to detail, especially around data quality, accuracy and interpretation.\n\n \n Desirable \n\n • Experience using Salesforce and understanding of how CRM data can support analytics and decision-making.\n, • Understanding of customer insight, market research, customer experience or NPS measurement.\n, • Working knowledge of cloud computing concepts and cloud-based visual or analytical environments.\n, • Understanding of data architecture concepts, including data warehousing and data lakes.\n, • Exposure to cloud computing environments such as Microsoft Azure.\n, • Exposure to predictive analytics, machine learning, AI-enabled analytics or advanced statistical methods.\n, • Experience working with customer, commercial, subscription, product usage or behavioural datasets.\n\n \n Behaviors and Mindset: \n\n • Demonstrates curiosity by asking thoughtful questions, challenging assumptions and looking for better ways to use data to understand customers and business performance.Demonstrates curiosity by asking thoughtful questions, challenging assumptions and looking for better ways to use data to understand customers and business performance.Demonstrates curiosity by asking thoughtful questions, challenging assumptions and looking for better ways to use data to understand customers and business performance.\n, • Shows a willingness to learn new tools, techniques and technologies, including Python, SQL, Power BI, automation, data science and AI-enabled analytics.\n, • Uses evidence objectively, explaining what the data does and does not show, and avoids jumping to conclusions without enough context.\n, • Maintains high standards of data quality, accuracy and interpretation so that insight and recommendations are reliable.\n, • Works collaboratively across Customer Insights, Product, Commercial, Technology and Data teams to build a more joined-up view of the customer.\n, • Shares learning openly, seeks input from others and helps translate business questions into clear analytical approaches.\n, • Acts with agility by adapting to changing priorities, working through ambiguity and staying focused on the most useful and practical answer.\n, • Takes ownership for moving work forward, raising issues early and identifying opportunities to improve reporting, automation or insight.\n, • Connects analysis to customer value and business outcomes, making sure insight supports better decisions and practical action.\n, • Shows confidence to test, learn and try new approaches, even when the answer is not perfect first time.\n\n \n Working for you: We know that your wellbeing and happiness are key to a long and successful career. These are some of the benefits we are delighted to offer: \n\n • Generous holiday allowance with the option to buy additional days\n, • Health screening, eye care vouchers and private medical benefits\n, • Wellbeing programs\n, • Life Assurance\n, • Access to a competitive contributory pension scheme\n, • Save As You Earn share option scheme\n, • Travel Season ticket loan\n, • Electric Vehicle Scheme\n, • Optional Dental Insurance\n, • Maternity, paternity and shared parental leave\n, • Employee Assistance Programme\n, • Access to emergency care for both the elderly and children\n, • RECARES days, giving you time to support the charities and causes that matter to you\n, • Access to employee resource groups with dedicated time to volunteer\n, • Access to extensive learning and development resources\n, • Access to employee discounts scheme via Perks at Work\n\n

About the team \n Elsevier’s mission is to help researchers, clinicians, and life sciences professionals advance discovery and improve health outcomes through trusted content, data, and analytics. As the landscape of science and healthcare evolves, we are pioneering intelligent discovery experiences — from Scopus AI and LeapSpace to ClinicalKey AI, PharmaPendium, and next-generation life sciences platforms. These products leverage retrieval-augmented generation (RAG), semantic search, and generative AI to make knowledge more discoverable, connected, and actionable across disciplines. The Search & AI Evaluation team sits within the Platform Data Science organization and is responsible for advancing enterprise-scale search, retrieval, and evaluation capabilities across Elsevier's global products. \n \n About the role \n We are looking for a Senior Data Scientist I to lead the development and evaluation of advanced search and generative AI systems. You will own complex problem areas end-to-end, drive methodological rigor in evaluation, and contribute to the technical direction of retrieval and RAG systems. \n \n This role is ideal for someone with deep hands-on experience in search/retrieval systems, RAG pipelines, and evaluation frameworks, who is ready to operate as a senior individual contributor with growing technical leadership responsibilities. \n \n Key responsibilities \n Search & Retrieval Development \n\n • Play a leading role in the design and optimization of lexical, vector, and hybrid retrieval systems at scale.\n, • Help architect and improve RAG pipelines, including retrieval strategies, prompt design, and system orchestration (e.g., LangGraph-based workflows).\n, • Help drive experimentation with embeddings, re-ranking models, and retrieval architectures to significantly improve relevance and user outcomes.\n, • Partner with engineering to ensure robust, scalable, and production-ready implementations.\n\n \n Evaluation & Experimentation \n\n • Help define and evolve evaluation strategies for search and generative AI systems across products.\n, • Help design robust frameworks for:\n, • IR evaluation (e.g., NDCG, recall, ranking quality)\n, • GenAI evaluation (e.g., grounding, faithfulness, hallucination detection)\n, • Contribute to development of evaluation datasets, gold standards, and annotation strategies.\n, • Guide and review experimental design, including offline evaluation and A/B testing, ensuring statistical rigor and validity.\n, • Contribute to responsible AI practices, including bias, fairness, and risk evaluation\n\n \n Generative AI & Applied Research \n\n • Apply and adapt state-of-the-art techniques in NLP, embeddings, and generative AI to production use cases.\n, • Evaluate and integrate emerging technologies into the team’s roadmap.\n, • Contribute to knowledge graph and semantic enrichment efforts that support retrieval systems.\n\n \n Domain & Research Integration \n\n • Collaborate with domain experts, ontology engineers, and biomedical informaticians to integrate scientific taxonomies, citation networks, and clinical ontologies into retrieval systems.\n, • Incorporate structured data — including datasets, chemical entities, genes, drugs, clinical trials, and patient outcomes — into AI-powered discovery pipelines.\n, • Advance Elsevier’s knowledge graph and metadata integration strategy, linking research and health data for more context-aware retrieval.\n, • Apply cutting-edge research in information retrieval, NLP, embeddings, and generative AI to continuously evolve Elsevier’s discovery and evaluation stack.\n\n \n Collaboration & Delivery \n\n • Work closely with product, engineering, and domain experts to define and deliver impactful solutions.\n, • Communicate findings and recommendations clearly to both technical and non-technical stakeholders.\n, • Take ownership of projects from problem definition through experimentation and deployment.\n\n \n Required qualifications \n\n • Master’s or PhD in Computer Science, Data Science, Machine Learning, or a related field (or equivalent practical experience)\n, • Experience in data science, machine learning, or applied NLP\n, • Strong hands-on experience with:\n, • Search and retrieval systems (lexical, vector, hybrid)\n, • RAG pipelines and LLM-based systems\n, • Evaluation methodologies for ML / IR / GenAI\n, • Advanced programming skills in Python\n, • Experience with modern ML/NLP frameworks (e.g., PyTorch, Hugging Face, LangChain, LangGraph, Haystack)\n, • Experience working with Databricks or similar distributed data/ML platforms\n, • Strong understanding of experimentation design and statistical analysis\n\n \n Preferred qualifications \n\n • Batchelor's, Masters, PhD in Computer Science, Data Science, Machine Learning, or a related field\n, • Experience working with large-scale datasets (scientific, biomedical, or enterprise data)\n, • Familiarity with scientific ontologies and metadata standards (e.g., MeSH, UMLS, ORCID, CrossRef)\n, • Exposure to production ML systems and MLOps practices\n, • Familiarity with data visualization and analytical tooling (e.g., Tableau, Power BI, matplotlib, seaborn, or similar) to communicate insights effectively\n, • Experience with human-in-the-loop evaluation or annotation workflows\n, • Publications or demonstrated applied research in IR, NLP, or generative AI\n\n \n Why join us? \n Join our team and contribute to a culture of innovation, collaboration, and excellence. If you are ready to advance your career and make a significant impact, we encourage you to apply. \n \n Work in a way that works for you \n We promote a healthy work/life balance across the organization. We offer an appealing working prospect for our people. With numerous wellbeing initiatives, shared parental leave, study assistance and sabbaticals, we will help you meet your immediate responsibilities and your long-term goals. \n\n • Flexible working hours - flexing the times when you work in the day to help you fit everything in and work when you are the most productive.\n\n \n Working for you \n We know that your well-being and happiness are key to a long and successful career. These are some of the benefits we are delighted to offer: \n\n • Holiday allowance with the option to buy additional days\n, • Health screening, eye care vouchers and private medical benefits\n, • Life assurance, plus optional additional life cover and spouse's life cover at own cost\n, • Access to a competitive contributory pension scheme\n, • Save As You Earn share option scheme\n, • Access to optional self funded benefits, including electric vehicle scheme, cycle to work scheme, dental insurance, critical illness cover, health cash plan, personal travel insurance\n, • Travel season ticket loan\n, • Paid time off when you become a parent, and paid time off for carers\n, • Support for personal and work-related challenges\n, • Access to emergency care for both the elderly and children\n, • Time off to support the charities and causes that matter to you\n, • Awards to recognize key service milestones\n\n \n About the business \n As a global leader in information and analytics, we help researchers and healthcare professionals advance science and improve health outcomes for the benefit of society. Building on our publishing heritage, we combine quality information and vast data sets with analytics to support visionary science and research, health education, and interactive learning, as well as exceptional healthcare and clinical practice. At Elsevier, your work contributes to the world’s grand challenges and a more sustainable future. We harness innovative technologies to support science and healthcare to partner for a better world.