Trabajos scientist en Reino Unido

Biometric Research Scientist / Actuary. Pacific Life Re's Strategic Analytics team is seeking a Biometric Research Scientist / Actuary to support research into mortality, morbidity, and disability risk. Collaborate with actuaries, underwriters, medical specialists, and data scientists across the

hackajob is partnering directly with Google to hire for this role. \n As an organization, Google maintains a portfolio of research projects driven by fundamental research, new product innovation, product contribution and infrastructure goals, while providing individuals and teams the freedom to emphasize specific types of work. As a Research Scientist, you'll setup large-scale tests and deploy promisi... \n\n \n\n \n \n ZIPC1_UKTJ

hackajob is partnering directly with BNY Mellon to hire for this role. \n In this role, you'll make an impact in the following ways: \n\n • Lead complex, end to end AI solution development. On BNY's AI platform ELIZA-from problem shaping and experimentation to deployment, adoption, and measurable business impact.\n, • Provide technical direction to pods; guide prioritization, trade offs, and architecture decisions...\n\n \n ZIPC1_UKTJ

hackajob is partnering directly with Google to hire for this role. \n We are hiring a research scientist to lead governance research and risk modeling work for the Frontier Safety Framework (FSF). \n The FSF is Google's framework for addressing possible severe risks from its frontier AI models. Both risk modeling and governance innovation are key to its continued success. Risk modeling helps Google under... \n \n \n \n \n ZIPC1_UKTJ

AI ACCELERATORMost diseases are still poorly understood at a biological level. Despite decades of research, the causal mechanisms driving many conditions remain unclear, limiting our ability to identify the right targets, design the right interventions and bring the right medicines to patients. The AI Accelerator exists to change that. Based in London and sitting within Computational Innovation (@computationalinnovation), a global organisation spanning computational biology, human genetics, data excellence and AI, the Accelerator’s mission is to build production-quality AI capabilities that deepen our understanding of disease biology and increase probability of success. We do this by applying neural-based methods across the biomedical data landscape to integrate heterogeneous, multimodal data sources, infer biological relationships and embed causal thinking into what we build. The goal is not just to predict but to explain and understand why disease occurs. It could be electronic health records and medical imaging to support patient segmentation. It could be ‘omics data to identify novel therapeutic targets. It could be predicting transcriptional change for a given disease-causing variant. It could be simulating the effect of modulating a target of interest. A core component of the AI Accelerator is AI Systems, a team focused on designing, building and deploying multimodal foundation models across the vast biomedical data landscape that will be used within Computational Innovation to enhance and accelerate portfolio decision-making. THE POSITIONWe are seeking a Staff AI Scientist to join AI Systems within Computational Innovation’s AI Accelerator. In this role, you will design and develop state of the art biomedical foundation models that learn rich representations from multi-omics, clinical and imaging data, advancing the field while directly enabling downstream teams to deploy AI capabilities to computational biologists and human geneticists that segment patient populations, uncover novel, disease-driving biology and ground that biology in genetics. You will be a highly experienced, independent AI Scientist within AI Systems, owning complex research workstreams and contributing meaningfully to the scientific direction of the team. Working within the wider research strategy and architectural vision set by the Senior Staff AI Scientist, you will own significant research programmes and bring deep specialist expertise across AI-driven life sciences, growing your influence over the team’s broader research agenda over time. This is a hands-on role with responsibility for leading a multidisciplinary squad that executes on AI Accelerator initiatives. You will work in close partnership with ML Engineers throughout the research and implementation process and contribute to the development of more junior AI Scientists. KEY RESPONSIBILITIESOwn and lead significant research workstreams in multimodal biomedical foundation model design, bringing deep specialist expertise across at least two biomedical data modalities from multi-omics, clinical and health records, medical imaging. Develop and validate novel approaches for learning from biomedical data, producing well-documented and reproducible research that ML Engineers can implement effectively. Design and run rigorous experiments to test multi-modal model architectures, training approaches and methods, interpreting results with scientific rigour and validating outputs against biomedical expectations as well as statistical benchmarks. Work closely with the Applied AI teams and computational biologists and human geneticists to understand needs and ensure models are developed with downstream therapeutic applications in mind. Work closely with ML Engineers throughout the research and implementation process, ensuring architectural decisions are scientifically ambitious, practically feasible and accurately reflected in production model components. Publish research findings in peer-reviewed ML and biomedical AI venues, contributing to the team’s scientific credibility and external profile. Mentor Senior AI Scientists by providing technical guidance, reviewing experimental designs and helping them develop greater research independence. REQUIREMENTSPhD in machine learning, computer science, computational biology, bioinformatics or a related quantitative field, with a strong publication record in ML or biomedical AI venues relative to career stage. Deep understanding of typical foundation model architectures such as transformers and expertise in self-supervised learning, pre-training, transfer learning and fine-tuning. Strong software engineering practices, including clean, testable, well-documented and reproducible research code, with proficiency in Python and deep learning frameworks such as PyTorch or JAX. Familiarity with distributed training frameworks and large-scale biomedical data processing, with demonstrated ability to take research from novel idea through rigorous experimentation to validated prototype. Strong ability to engage with computational biology and human genetics questions in the context of drug discovery and translate them into research directions that deliver meaningful capability to Applied AI and Analytics. Experience operating in a matrixed setting as a technical lead. WHY THIS IS A GREAT PLACE TO WORKBoehringer Ingelheim has been recognised as a Top Employer in the UK, demonstrating our commitment to building an exceptional workplace through strong people practices and supportive HR policies.To learn more about why BI is a great place to work, visit:

About usGoCardless is a global bank payment company. Over 100,000 businesses, from start-ups to household names, use GoCardless to collect, manage and send bank payments through Direct Debit, real-time payments and open banking. With US$130bn+ processed annually across 30+ countries, we handle recurring and one-off payments without the chasing, stress, or expensive fees. Our end-to-end payment platform also features AI-powered solutions to improve payment success and reduce fraud, alongside connections to over 350 platforms businesses use everyday.We are headquartered in the UK, with teams and operations spanning North America, Europe and Asia-Pacific.The roleThis role will be working at the heart of the GoCardless product in our Payment Flows team, within the Bank Payment Network Group. The team ensures that merchant money is settled quickly, with high certainty, on every payment scheme we provide. You will define and build propositions that provide market leading outcomes: building the capabilities to settle money faster, leveraging ML to confirm payments sooner, and unlocking payment capabilities that give merchants the best experience.The Senior Product Manager will work closely with the team’s Engineering Manager and Data Scientist to lead the product improvements that help our customers and drive revenue. You will also collaborate closely with Product Marketing, Customer Success, and other Product teams to achieve great outcomes for our customers and work towards our product vision.What excites you Delivering customer and business value: Being relentlessly focused on understanding and solving the customer problems which result in them using GoCardless as much as they can.Problem discovery and prioritisation: Taking complex and ambiguous product problems and structuring these effectively. This includes clearly defining the problem space, the impact of the problem and your prioritisation process.Data-led decision-making: Using quantitative and qualitative evidence to support your decisions and opportunity identification.Defining Product Strategy: Identifying key customer segments, and our approach to meeting their needs over the longer term in ways that create value for them and GoCardlessInfluencing and communication: Building collaborative relationships with your team, stakeholders and executives to deliver change effectively across your remit. This includes growing to become the ‘go-to’ person for your product area; translating complex, technical problems into understandable concepts; and convincing stakeholders of the best approach using structured reasoning.Leadership: Setting direction and coordinating action across a range of teams and functionsShipping stuff: Working with your team to support changes to completion, delivering consistent positive impact across your product area. Being comfortable delivering a range of projects: from MVP experiments testing a hypothesis to a new feature.What excites us Delivery of impact: You are focused on delivering business value through experimentation and have experience of doing that.Exceptional problem-solving and analytical skills: We want our Product Managers to have an outstanding ability to tackle valuable customer and business problems. At GoCardless we start by asking ‘why?’, and a data-led approach is central to how we run Product. You have a customer centric approach and are comfortable with qualitative and quantitative analysis.High agency: We’re after people who aren’t afraid of a challenge and will take ownership of problems they come across and help to resolve them and adapt to a constantly changing environment.Collaborative leaders: Product roles bring responsibility without direct authority. We’re looking for leaders who can motivate and earn the trust of stakeholders and teams with a collaborative approach.We don’t expect you to meet every requirement. If you’re excited by this role, we encourage you to apply.Base salary range: 100,000 - 150,000Base salary ranges are based on role, job level, location, and market data. Please note that whilst we strive to offer competitive compensation, our approach is to pay between the minimum and the mid-point (100,000 - 125,000) of the pay range until performance can be assessed in role. Offers will take into account level of experience, interview assessment, budgets and parity between you and fellow employees at GoCardless doing similar work.(some of) The good stuffWellbeing - stay healthy with dedicated support and medical coverWork away scheme - gives you the option to work away from your country of residence for up to 90 days in any 12 month periodAdaptive Working - allows you to work flexibly, around your lifestyleParental leave - to suit everyone embarking on life's great adventureLearning Budget - lead your own development with an annual learning budgetTime off - generous holiday allowance, + 3 annual volunteer days, + 4 annual business-wide wellness days (‘GC Fridays’)Life at GoCardless We're an organisation defined by our values; We start with why before we begin any project, to ensure it’s aligned with our mission. We act with integrity, always. We care deeply about what we do and we know it's essential that we be humble whilst we do it. Working this way creates the GC magic- the reason we all love showing up to work. Diversity & InclusionAs of April 2025, we had 806 employees (GeeCees) globally, with 524 based in the UK, 163 based in Latvia and 119 across our other offices.To ensure that we're representative of the world around us - and to be able to review relevant benchmarks - we ask GeeCees to voluntarily disclose diversity data. This year, the proportion of GeeCees providing data increased to 88% (up from 79% in 2024). With regards to diversity within GoCardless, we can see GeeCees identifying as:Asian, Black, Mixed or Other — 25%Neurodiverse — 9%LGBTQIA+ — 9%Disabled — 1%Average age — 33Female — 45%Male — 55% We’re rooting for you during your application and GoCardless aims to provide reasonable adjustments to make our recruitment process as remarkable and accessible as we can. Please speak to your Talent Partner if you need extra support.If you want to learn more, you can read about our Employee Resource Groups and objectives hereSustainabilityWe’re committed to reducing our impact on the environment, leaving a more sustainable world for future generations. Check out our sustainability action plan here.Find out more about Life at GoCardless via Twitter, Instagram and LinkedIn.

Company DescriptionWe’re ASOS, the online retailer for fashion lovers all around the world. We exist to give our customers the confidence to be whoever they want to be, and that goes for our people too. At ASOS, you’re free to be your true self without judgement, and channel your creativity into a platform used by millions. But how are we showing up? We’re proud members of Inclusive Companies, are Disability Confident Committed and have signed the Business in the Community Race at Work Charter and we placed 8th in the Inclusive Top 50 Companies Employer list. Everyone needs some help showing up as their best self. Let our Talent team know if you need any adjustments throughout the process in whatever way works best for you. Job DescriptionWe're looking for an Applied Scientist to join the team – whose mission is to build machine learning capabilities that power better decisions, experiences and outcomes across ASOS.You'll work on challenging real-world machine learning problems, developing scalable models and intelligent systems that support a range of business domains.As an Applied Scientist, you'll work alongside data engineers, ML engineers, analysts, product managers and business stakeholders to design, develop and deploy machine learning solutions at scale. You'll have the opportunity to influence both the scientific direction of our ML capabilities and the products they enable.Key ResponsibilitiesDesign, develop and deploy machine learning models and data-driven solutions in production environments.Apply machine learning and optimisation techniques to solve complex business problems.Partner with engineers to productionise models and build reliable, scalable ML systems.Design and analyse experiments and evaluation frameworks to measure model performance and business impact.Explore, evaluate and prototype new approaches from both industry and academia.Work closely with product and business stakeholders to identify opportunities where machine learning can create value.Contribute to the team's technical and scientific direction through knowledge sharing, code reviews and collaboration.Help shape best practices in machine learning, experimentation and applied research across the organisation.QualificationsAbout YouYou'll enjoy applying machine learning to large-scale, real-world challenges and translating research into production systems that deliver measurable impact.We'd be particularly interested in candidates who bring experience in some of the following areas:Developing and deploying machine learning models in production environments.Applying statistics, analytics and machine learning techniques to solve complex business problems.Experience in one or more of the following areas:Developing and applying machine learning solutions to solve complex business problems.Building predictive models, intelligent systems or decision-support capabilities using large-scale data.Translating research, experimentation and analytical insights into production-ready solutions.Designing and evaluating models using appropriate performance, business and customer impact measures.Working across the end-to-end machine learning lifecycle, from problem definition and experimentation through to deployment and monitoring.Applying quantitative, statistical or optimisation techniques to support decision-making and product development.Proficiency in Python and modern machine learning frameworks such as PyTorch, TensorFlow or similar.Experience working with large datasets and distributed data processing systems.Strong software engineering practices, including testing, version control and maintainable code.Ability to communicate technical concepts to both technical and non-technical audiences.Curiosity, pragmatism and a willingness to learn, experiment and share knowledge.Experience bringing ML products from ideation through to production.Experience working in fast-paced, product-driven environments.Familiarity with cloud-native ML platforms and MLOps practices.Publications, open-source contributions or evidence of staying current with developments in machine learning and AI.Additional InformationBeneFITS’ Employee discount (hello ASOS discount!) Employee sample sales 25 days paid annual leave + an extra celebration day for a special moment Private medical care scheme Fixed Annual Payment in addition to your salary each year, it's just an extra thank you from us Opportunity for personalised learning and in-the-moment experiences that enable you to thrive and excel in your role SummaryType: Full-timeFunction: Information TechnologyExperience level: Mid-Senior LevelIndustry: Retail

hackajob is partnering directly with Google to hire for this role. \n We aim to turn production data into intelligence on the safety of deployed AI models. Safety Oversight is a new team tasked with using large-scale production traffic and a variety of automated evaluation methods to monitor the safety and alignment of deployed models. Our work will ensure we measure the real-world efficacy of our saf... \n \n \n \n ZIPC1_UKTJ

hackajob is partnering directly with Kainos to hire for this role. \n Join Kainos and Shape the Future \n At Kainos, we're problem solvers, innovators, and collaborators - driven by a shared mission to create real impact. Whether we're transforming digital services for millions, delivering cutting-edge Workday solutions, or pushing the boundaries of technology, we do it together. \n \n We believe in a people-fir... \n \n \n \n \n ZIPC1_UKTJ

hackajob is partnering directly with Accenture to hire for this role. \n YOU ARE \n As an AI/ML Computational Scientist, you will design, build, and operationalize artificial intelligence and machine learning solutions for enterprise clients, combining custom models with cloud and third-party AI services to deliver production-ready outcomes. Your role spans the full solution lifecycle - assessing client ... \n \n \n ZIPC1_UKTJ

hackajob is partnering directly with LexisNexis to hire for this role. \n Senior Data Scientist I \n Excited to uncover insights from complex data and turn them into impactful business decisions? \n Do you enjoy building predictive models, experimenting with advanced analytics, and solving real-world challenges with data? \n About the team: \n LexisNexis Intellectual Property Solutions (LNIP) is the global leader i... \n \n \n \n ZIPC1_UKTJ

hackajob is partnering directly with Simply Business to hire for this role. \n Who Are We? \n We insure small businesses and enable big dreams - not just for our customers, but for our people and communities too. With over 1,000,000 active insurance policies, we protect builders, bakers, landlords and more than 1,200 other trades. \n We're a technology company as well as one that sells insurance. That means w... \n \n \n \n ZIPC1_UKTJ

Here's a summary of the role Data is only powerful when everyone agrees what it means. This is your chance to build a world class product behavioural data system and process from the ground up. We're rebuilding the internal product our teams use to measure product success and end-user value across all our 24+ products in four business units. You'll design the single source of truth: the metric definitions, the telemetry standards, the data contract engineering instruments against, the change governance processes and tooling, and the models that turn behaviour into portfolio insight. You'll educate and support the teams using this internal behavioural data product to set expectations and and plot a rational roadmap for the maturing of this product, helping our user to use the data honestly and wisely. Usage tells you what happened, not why, or whether it mattered. We want someone who sets quantitative behaviour against qualitative evidence and treats the disagreement as the interesting part. AWS/Snowflake is our spine; capture and BI are open decisions you'll help make. Your models feed the business reviews our executive team, CTO and investors use to run the portfolio, and engineering is committed to instrument against your contract. Here's what your first twelve months should look like First 90 days. Learn the estate, meet the engineers who instrument it, and agree the measurement model for one product end to end — with a defensible adoption number and the qualitative read on what it means. Three to six months. Data contract published, instrumentation spec landed with engineering, first business unit building against it. Definitions, naming and versioned change control governed. Six to twelve months. Rolling out across the remaining business units through the BU-aligned analysts, portfolio reporting running on your numbers. Here's a breakdown of what you'll do (not all of it, just the important stuff) Design the behavioural telemetry — event and entity-state schemas at a grain that supports both portfolio roll-up and feature-level decisions — and write the instrumentation specification engineering builds against. Then assure what comes back: coverage, freshness, reconciliation. Own the measurement standard — canonical definitions, naming, field ownership, versioned change control — across every business unit. Build the models — SQL, BI and roll-up logic turning behaviour into insight on adoption, time-to-value and value realisation. Triangulate. Pair behavioural data with qualitative evidence from design research and VoC, segment by user role and account, and say so publicly when the two disagree. Partner on the product, customer and user taxonomies, set the technical standard for the BU-aligned analysts, and help shape the analytics stack as we revamp it. These are the essentials you'll need to get an interview Direct experience building mixed-method behavioural insight systems — you've built the layer where quantitative behaviour and qualitative evidence come together, not just consumed the output. You've worked alongside design or UX researchers, and can name a time the qualitative read changed what you measured. Hands-on event and telemetry schema design — Pendo, Amplitude, Segment, Mixpanel or equivalent. You designed the schema and wrote the spec, not used dashboards someone else built. Designing and governing product data models and taxonomies — canonical metrics and naming taken into a multi-product estate and made to stick, including acquired products. Data governance practice: schema and field ownership, versioned change control, standards adoption across teams you don't own. Fluency in SQL and the BI / warehouse layer — you build and validate roll-up logic yourself. Behavioural segmentation judgement — you know why a B2B account is a mix of people with different motivations, and why averaging them produces confident, wrong conclusions. The credibility to influence without authority — you can hold a standard with teams you don't line-manage. It would be great if you had these too, but we'll support you if you don't Hands-on behavioural analytics and synthesis practice — running the analysis yourself, not only building what enables it. Privacy and lawful basis as live design constraints — pseudonymisation, residency, re-identification controls. GRC, governance or regulated-software domains. Salesforce, Jira Product Discovery, Pendo, and consolidating fragmented tooling into one system of record. Product value / ROI measurement — connecting behaviour to commercial outcomes. How we'll assess this We ask everyone to write SQL and design an event schema, and to talk us through a time qualitative evidence contradicted their numbers. No take-home longer than an hour. Here's where this role goes next We're building this function, not maintaining it. You set the standard the BU-aligned analysts land across the business — technical leadership from day one, without a management line. As the team grows around you — a data scientist, a behavioural researcher, an ML engineer — the routes are principal-level ownership of product behavioural data across Diligent, or leading the team that runs it. We'd rather be straight with you than promise a title we cannot yet name. The scope is real, and it is expanding. #LI-HybridAbout UsDiligent is the AI leader in governance, risk and compliance (GRC) SaaS solutions, helping more than 1 million users and 700,000 board members to clarify risk and elevate governance. The Diligent One Platform gives practitioners, the C-Suite and the board a consolidated view of their entire GRC practice so they can more effectively manage risk, build greater resilience and make better decisions, faster. At Diligent, we're building the future with people who think boldly and move fast. Whether you're designing systems that leverage large language models or part of a team reimaging workflows with AI, you'll help us unlock entirely new ways of working and thinking. Curiosity is in our DNA, we look for individuals willing to ask the big questions and experiment fearlessly - those who embrace change not as a challenge, but as an opportunity. The future belongs to those who keep learning, and we are building it together. At Diligent, you’re not just building the future - you’re an agent of positive change, joining a global community on a mission to make an impact.Learn more at diligent.com or follow us on LinkedIn and FacebookWhat Diligent Offers YouCreativity is ingrained in our culture. We are innovative collaborators by nature. We thrive in exploring how things can be differently both in our internal processes and to help our clientsWe care about our people. Diligent offers a flexible work environment, global days of service, comprehensive health benefits, meeting free days, generous time off policy and wellness programs to name a fewWe have teams all over the world. We may be headquartered in New York City, but we have office hubs in Washington D.C., Vancouver, London, Galway, Budapest, Munich, Bengaluru, Singapore, and Sydney.Diversity is important to us. Growing, maintaining and promoting a diverse team is a top priority for us. We foster and encourage diversity through our Employee Resource Groups and provide access to resources and education to support the education of our team, facilitate dialogue, and foster understanding.Diligent created the modern governance movement. Our world-changing idea is to empower leaders with the technology, insights and connections they need to drive greater impact and accountability – to lead with purpose. Our employees are passionate, smart, and creative people who not only want to help build the software company of the future, but who want to make the world a more sustainable, equitable and better place. Headquartered in New York, Diligent has offices in Washington D.C., London, Galway, Budapest, Vancouver, Bengaluru, Munich, Singapore and Sydney. To foster strong collaboration and connection, this role will follow a hybrid work model. If you are within a commuting distance to one of our Diligent office locations, you will be expected to work onsite at least 50% of the time. We believe that in-person engagement helps drive innovation, teamwork, and a strong sense of community.Diligent is proud to be an equal opportunity employer. We do not discriminate based on race, color, religious creed, sex, national origin, ancestry, citizenship status, pregnancy, childbirth, physical disability, mental disability, age, military status, protected veteran status, marital status, registered domestic partner or civil union status, gender (including sex stereotyping and gender identity or expression), medical condition (including, but not limited to, cancer related or HIV/AIDS related), genetic information, or sexual orientation in accordance with applicable federal, state and local laws. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. See also Diligent's EEO Policy and US EEOC’s Know Your Rights. We are a drug free workplace. We are committed to providing reasonable accommodations for qualified individuals with disabilities and disabled veterans in our job application procedures. If you need assistance or an accommodation due to a disability, you may contact us at recruitment@diligent.com. To support a fair and consistent hiring process, we use AI and digital automated tools to assist our recruitment team in organizing candidate data, surfacing relevant applications, coordinating interview scheduling and summarizing interview notes. All final screening, evaluation, and hiring decisions are made by humans on our team. To learn more about how we collect, protect, and process your information, please review our Candidate Privacy Policy. At Diligent, we recognize the value of a diverse global workforce. Visa sponsorship may be available for select positions based on business needs and specific role requirements. Sponsorship decisions are evaluated on a case-by-case basis, and eligibility should not be assumed for all opportunities. Recruitment agencies: Diligent does not accept unsolicited agency resumes. Please do not forward resumes to our jobs alias, Diligent employees or any other organization location. Diligent is not responsible for any fees related to unsolicited resumes

We are recruiting for a Senior Data Scientist on behalf of a market leading Lloyd's Syndicate. \n The successful candidate will strengthen the business's data science capability by delivering models and insights that improve underwriting profitability, automation and efficiency. It is a true end-to-end role, owning projects from problem framing through to deployment and ongoing model performance, with strong object-oriented programming, machine learning and statistical skills, and experience taking models into production, designing ML pipelines and working with MLOps, CI/CD and Azure. \n Key Responsibilities \n Delivery of data science products \n\n • Leading data science projects end-to-end, from problem framing through development, deployment and ongoing monitoring in production.\n, • Working alongside the actuarial team and coordinating with the Data Science and Data Analytics Manager to support the business with proactive analytics and insights.\n, • Using generative AI to enrich insight and unlock new opportunities, deployed and maintained through the same MLOps patterns applied to traditional models.\n\n Engineering and MLOps standards \n\n • Designing, building and maintaining machine learning pipelines in a cloud environment, applying sound software engineering practice.\n, • Owning deployed models in life, monitoring performance and drift, and ensuring models are documented and explainable to a standard appropriate for a regulated environment.\n\n Stakeholder engagement and requirements \n\n • Working with technical and non-technical stakeholders to identify, document, analyse and prioritise requirements for data science products.\n, • Producing clear deliverables and communicating findings and their limitations to audiences without a technical background.\n\n Team and capability building \n\n • Coaching and upskilling data scientists and data analysts through code review, pairing and mentoring, and contributing to the data science backlog and roadmap.\n\n Key Requirements \n Essential \n\n • Strong Python, written to production standard, with object-oriented design and software engineering fundamentals: version control, code review, automated testing, dependency and environment management.\n, • Machine learning across the standard toolkit (scikit learn, pandas, NumPy, statsmodels or equivalents), with sound judgement about model selection, validation and the limits of what the data supports.\n, • MLOps and CI/CD in practice, covering pipeline orchestration, model versioning, automated deployment, monitoring and retraining.\n, • Cloud based machine learning delivery, ideally on Azure (Azure ML, Azure DevOps), with equivalent AWS or GCP experience considered.\n, • SQL and relational data modelling, with the ability to work efficiently against large datasets.\n, • Statistical foundations sufficient to design sound experiments, quantify uncertainty and challenge conclusions that the data does not support.\n\n Desirable \n\n • Insurance experience (specifically in the Lloyd's market), pricing or underwriting in a regulated environment.\n, • Practical experience deploying generative AI or LLM based solutions.\n\n Altogether, this role suits a hands-on data scientist who can own the full lifecycle from problem framing to production and translate that work into commercial value alongside underwriters and actuaries. \n We do not retain any personal information without your permission. Please refer to our data protection policy on our official website for more information.

\n SENIOR DATA SCIENTIST \n UP TO £70,000 + EQUITY \n LONDON \n HYBRID WORKING - 2 DAYS PER WEEK \n Join a fast-growing fintech redefining lending through smarter, more personalised credit decisions. Take ownership of end-to-end modelling and shape how data directly drives real-world lending outcomes. \n THE COMPANY \n A UK-based fintech lender building an innovative consumer lending product focused on flexibility and affordability. The business is customer-first, using income and affordability data to make fairer lending decisions beyond traditional credit scores. With a proven model in place and strong growth plans, they offer a unique opportunity to join at an early but established stage. \n THE ROLE \n As a Senior Data Scientist, you will take ownership of credit risk and decisioning models, working across the full lifecycle from development through to deployment. This is a highly hands-on role with significant influence on how data drives commercial lending decisions. \n Specifically, you can expect to be involved in: \n\n • Building and optimising credit risk models, including scorecards and machine learning approaches\n, • Deploying models into production and monitoring performance over time\n, • Developing data pipelines and integrating multiple data sources into decisioning frameworks\n, • Working closely with stakeholders to ensure models directly influence lending strategy and outcomes\n\n SKILLS AND EXPERIENCE \n\n • Strong experience developing credit risk models, including scorecards and ML models\n, • Proficiency in Python and SQL for data analysis, modelling, and data manipulation\n, • Experience working with cloud-based infrastructure (e.g. AWS)\n, • Understanding of model deployment and production environments\n, • Ability to translate technical work into commercial lending and commercial insights\n, • Familiarity with financial services data such as bureau, Open Banking or affordability data\n\n BENEFITS \n The successful Senior Data Scientist will receive up to £70,000 and a comprehensive benefits package. \n

Research Physics Expert \n \n Location: Remote \n \n Engagement Type: Hourly Contract \n \n Compensation: $61–$77/hour \n \n About the Opportunity \n This opportunity is for experienced Physics Researchers interested in contributing to advanced AI research and evaluation projects. You will help develop and validate high-quality reference solutions for frontier-level physics benchmarks, ensuring that next-generation AI systems are evaluated against rigorous scientific standards. \n The work involves solving complex research-level physics problems, reviewing expert solutions, and contributing to the creation of human-verified benchmark data used to measure AI reasoning capabilities. \n Ideal Qualifications \n • PhD, Postdoctoral Researcher, Faculty Member, or Industry Research Scientist in Physics or a related field. \n • Expertise in one or more areas including High Energy Physics, Mathematical Physics, Biophysics, Statistical Physics, Condensed Matter Physics, AMO Physics, Cosmology, Astrophysics, Quantum Information, or Quantum Mechanics. \n • Strong publication record demonstrating research expertise in a relevant subfield. \n • Experience solving complex research-level physics problems and developing rigorous scientific analyses. \n • Proficiency with Python, Jupyter Notebooks, SymPy, and LaTeX. \n • Excellent analytical reasoning, problem-solving, and scientific communication skills. \n • Strong attention to detail and commitment to scientific accuracy. \n Responsibilities \n • Solve research-level physics problems and develop complete reference solutions. \n • Create structured problem decompositions and verification methodologies. \n • Author Python-based answer templates and automated validation functions. \n • Review and audit submitted solutions for correctness, rigor, and methodological soundness. \n • Provide detailed feedback to improve solution quality and benchmark reliability. \n • Adjudicate between competing solution approaches and determine final reference answers. \n • Document derivations, verification procedures, error tolerances, and scientific rationale. \n • Contribute to the development of high-quality benchmark datasets for evaluating frontier AI systems. \n Project Details \n • Expected commitment of approximately 10 hours per week. \n • Fully remote and asynchronous work environment. \n • Opportunity to collaborate with leading AI researchers and domain experts. \n • Long-term project engagement with potential extensions based on project needs. \n Compensation \n • Competitive compensation of $80–$135/hour. \n • Weekly payments. \n • Independent contractor engagement. \n Application Process \n\n • Submit your resume, publication record, or research background.\n, • Complete any required assessment or evaluation.\n, • Participate in the expert review process.\n, • Final selection and onboarding.\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

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

New Contract Opportunity for an eDV Cleared Data Scientist with an Industry-Leading National Security Consultancy in London. \n \n\n • Active eDV Required\n, • Up to £680 p/d Inside IR35\n, • 12-month engagement\n, • Urgent requirement - ASAP start\n, • 5 days on site in central London\n\n \n The Role: \n You will develop mission-critical data solutions for National Security clients. You will contribute to advanced projects across AI, cybersecurity, cloud, big data and digital transformation, helping to shape the future of national security. Working with datasets of varying scale, you will cleanse, integrate and analyse data to enable faster, more informed decision-making that supports the safety of the nation. \n \n Key Responsibilities: \n\n • Design and deliver data science solutions in support of national security operations.\n, • Develop and optimise pipelines to process large, complex datasets.\n, • Apply machine learning and statistical methods to generate actionable insight.\n, • Produce clear visualisations to communicate results to stakeholders.\n, • Work within agile teams to deliver robust, scalable systems.\n, • Support cloud deployments and integration into live operational environments.\n\n \n Seeking Experience in most of the following: \n\n • Python or similar scripting languages for data exploration and preparation.\n, • Machine learning and statistical methods, including model validation.\n, • Data analytics and visualisation techniques.\n, • Processing large datasets using batch or streaming tools such as Apache Spark.\n, • Data acquisition and fusion approaches.\n, • Cloud platforms (ideally AWS) and cloud-based data science solutions.\n, • DataOps principles and practices.\n, • Structured and unstructured databases.\n, • Container technologies, including Docker and Kubernetes.\n, • Agile delivery methods.\n, • Software engineering best practice, including version control and CI/CD pipelines.\n, • Linux environments.\n\n \n Why Apply? \n\n • Work on mission-critical UK Government projects with real-world impact\n, • Join a leading consultancy known for innovation and technical excellence\n, • Long-term engagement with competitive day rate and secure on-site 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

Campion Pickworth is partnering with a leading international professional services firm to hire a Data Scientist – Senior Consultant to join a high-performing Analytics & Data Science team. \n \n This is an opportunity to work at the forefront of Data Science, Machine Learning, Cloud Technologies and Generative AI, helping major organisations unlock value from their data and solve complex business challenges. You'll collaborate with talented specialists, work with modern technologies, and play a key role in delivering innovative solutions across a diverse project portfolio \n \n What You’ll Do: \n\n • Develop and deploy advanced analytics, data science, machine learning and agentic ai solutions across a variety of use cases\n, • Use technologies such as Python, R, Azure, Databricks, SQL, Power BI, and Tableau to extract actionable insights from complex datasets\n, • Contribute to the design and implementation of scalable data science workflows and best practices\n, • Collaborate with cross-functional stakeholders to understand business needs and translate them into effective analytical solutions\n, • Support multiple projects from exploration through to deployment within cloud-based environments\n, • Maintain high standards of code quality, documentation, and testing within a DevOps-oriented workflow\n, • Apply strong knowledge of ML techniques, from supervised/unsupervised learning through to emerging methods in generative ai and large language models\n\n \n What We’re Looking For: \n Essential Skills & Experience \n\n • Proven experience solving complex, real-world problems using data science and analytics\n, • Strong Python skills (pandas, numpy, scikit-learn) with a solid grounding in probability and statistics\n, • Deep understanding of machine learning methods and their practical application\n, • Experience delivering multiple end-to-end data science projects across varied data types and business domains\n, • Familiarity with DevOps practices and tools such as Git\n, • Cloud experience (e.g., Azure, AWS) and working with ML platforms and services\n, • Excellent communication skills, with the ability to explain complex concepts to non-technical stakeholders\n, • Ability to align analytical outputs with broader business objectives\n, • Someone with 1-3 years of industry experience\n\n \n Desirable Skills \n\n • Experience using R and NLP or deep learning techniques (e.g., TF-IDF, word embeddings, CNNs, RNNs)\n, • Familiarity with generative AI and prompt engineering\n, • Experience with Azure Databricks, MLflow, Azure ML services, Docker, or Kubernetes\n, • Experience working in large, complex organisations or regulated industries\n\n \n This role is unable to provide sponsorship

PhD & Academic Expert \n \n Position: PhD & Academic Expert \n \n Type: Hourly Contract \n \n Compensation: $245–$280/hour \n \n Location: Remote \n \n About the Opportunity \n This opportunity is for experienced PhD-level academic and research professionals across technical and humanities disciplines to contribute to advanced AI research and evaluation projects. \n You'll apply your subject-matter expertise to evaluate AI-generated responses, create expert-level prompts and reference answers, identify subtle errors and weaknesses in reasoning, and establish rigorous standards for evaluating AI performance. No prior AI experience is required — your academic and research expertise is what matters. \n The role is suitable for experts across fields including STEM, English, literature, journalism, social sciences, and other research-intensive disciplines. \n Responsibilities \n\n • Evaluate AI-generated responses for accuracy, depth, reasoning quality, and subject-matter expertise.\n, • Create high-quality expert prompts, reference answers, and detailed critiques.\n, • Identify subtle factual errors, gaps in reasoning, unsupported conclusions, and shallow analysis.\n, • Apply rigorous academic research standards when assessing AI-generated content.\n, • Develop evaluation criteria that distinguish expert-level reasoning from generic or surface-level responses.\n, • Analyze complex academic and research problems within your area of specialization.\n, • Provide clear, evidence-based written feedback to improve AI model performance.\n, • Contribute to the development of evaluation frameworks, research methodologies, and quality standards.\n, • Collaborate remotely with research and project teams to refine evaluation guidelines and deliverables.\n\n Required Qualifications \n\n • PhD in a relevant technical, academic, or humanities discipline.\n, • Strong background in academic research, critical analysis, and research methodology.\n, • Excellent ability to evaluate complex information for accuracy, depth, logic, and evidence.\n, • Strong academic and technical writing skills.\n, • Ability to identify nuanced errors and distinguish sophisticated reasoning from superficial analysis.\n, • Excellent written English and ability to communicate complex ideas clearly.\n, • Strong attention to detail and commitment to research-quality standards.\n, • Ability to work independently in a fully remote environment.\n\n Preferred Qualifications \n\n • PhD from a top-ranked university.\n, • Background in STEM, English, literature, journalism, or another research-intensive field.\n, • Experience with peer review, academic publishing, research supervision, or scholarly evaluation.\n, • Experience developing research frameworks, academic curricula, technical documentation, or evaluation criteria.\n, • Experience analyzing or evaluating AI-generated content is a plus, but not required.\n, • Based in an English-speaking country.\n, • Strong experience translating complex research findings into clear written explanations.\n\n Compensation \n\n • Competitive compensation of $245–$280/hour.\n, • Hourly contract engagement.\n, • Fully remote with flexible scheduling.\n, • Opportunity to contribute to cutting-edge AI research and evaluation projects.\n\n Application Process \n\n • Apply to the role\n, • Complete the required screening questions\n, • Submit academic and professional background information\n, • Complete the relevant evaluation or assessment\n, • Participate in the interview/evaluation stage\n, • Hiring team review and project onboarding\n\n

Director – Immunoassay Development \n \n On-site/ Hybrid | London/Stevenage | Permanent \n \n Talentmark is working with an innovative, early-stage diagnostics company developing next-generation at-home testing technology. \n \n We are looking for an Associate Director / Director – Assay Development to take ownership of assay development and help shape the company's scientific direction. This is a hands-on leadership role, taking assays from initial design and optimisation through to validation and commercialisation. \n \n The role is currently based in Stevenage, with the longer-term expectation that the company will be London-based. Candidates should therefore be comfortable commuting to Stevenage initially, with longer-term transition to London and hybrid working. \n \n Key Responsibilities \n\n • Lead the design and development of quantitative immunoassays.\n, • Drive optimisation of sensitivity, precision, reproducibility and stability.\n, • Design and execute assay development and validation studies.\n, • Maintain robust documentation aligned with regulatory and technical-file requirements.\n, • Establish high standards for data integrity, experimental rigour and statistical analysis.\n, • Manage external scientific collaborators and advisors.\n\n \n Your Background: \n \n You are an experienced immunoassay scientist with a strong industry leadership background in diagnostic assay development, with track record in taking assays through validation towards commercial release. \n \n Essential Experience \n \n\n • PhD in Biochemistry, Analytical Chemistry, Bioengineering, Biomedical Science or a related discipline.\n, • Industry experience in diagnostics or assay development (5 yrs+)\n, • Strong hands-on expertise in immunoassay development, particularly ELISA, with a good working knowledge of enzymatic assays.\n, • Experience translating laboratory immunoassays into point-of-care, lateral-flow, biosensor or microfluidic cartridge formats.\n, • Experience with low-concentration analyte measurement\n, • Proven experience developing diagnostic assays through validation and commercial release.\n, • Practical experience working with human biological samples (blood, saliva or urine).\n, • Ideal candidate would be London based but happy to commute to Stevenage\n\n \n Desirable Experience \n \n\n • Experience developing steroid or peptide hormone assays.\n, • Familiarity with freeze-drying / lyophilisation for reagent stabilisation.\n, • Knowledge IVD technical-file preparation for CE, UKCA or FDA submissions.\n, • Experience building or leading a laboratory/science team.\n, • Experience working with aptamer technology.\n\n \n What's on Offer \n \n\n • The opportunity to take diagnostic assays from concept through validation and towards market.\n, • A senior, hands-on role within an ambitious early-stage company.\n, • Competitive salary and share equity options scheme.\n\n \n Apply: \n \n It is essential that applicants hold entitlement to work in the UK. Please quote job reference 199 429 in all correspondence.

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.

Lead Data Scientist (Agentic AI) | Series-A Start-Up | £100,000-£130,000 DOE + Shares | London / Hybrid (1 Day Office) \n \n We’re partnering with a fast-growing AI tech scale-up expanding its team, who are hiring for a Lead Data Scientist (Agentic AI). \n \n This is a rare opportunity to lead the delivery of enterprise-grade Agentic AI solutions - working with ambitious clients at the forefront of applied AI innovation. \n \n The Company \n \n This pioneering organisation has built an advanced enterprise AI platform delivering predictive analytics and AI-powered decision intelligence. \n \n Their digital AI agents provide always-on, intelligent insights - supporting leading clients across financial services, retail, FMCG, pharma, and beyond to enhance performance and efficiency. \n \n The Role \n \n As Lead Data Scientist, you’ll lead the delivery of Agentic AI solutions post-sale, owning client projects from design through to deployment. This is a hands-on role combining strong technical depth with delivery leadership and stakeholder management. \n \n You’ll implement AI and agentic systems across enterprise clients, designing scalable architectures using LLMs, RAG pipelines, and agentic workflows, while working closely with engineering and product teams to ensure successful outcomes. \n \n The Candidate \n \n Key attributes of the suitable Lead Data Scientist include: \n \n\n • Technical Data Science Expertise – Strong background delivering production-grade solutions, ideally within consulting or product-led environments.\n, • Agentic AI & Modern AI Systems Experience – Hands-on exposure to LLMs, RAG pipelines, and agentic\n, • Delivery Leadership & Client Ownership – Comfortable leading teams while remaining technically involved and managing client relationships post-sale\n\n

Product Analyst \n London (Hybrid – 2x Days a Week in Office) \n £80,000-£90,000 \n Sponsorship - Available \n \n The Company \n \n Are you a commercially-minded Product Analyst or Product Data Scientist looking to make an impact in a fast-growing, PE-backed consumer tech business? This is a unique opportunity to join a company in an exciting growth phase, working alongside an experienced and data-driven leadership team! \n \n The Role \n \n You’ll sit within a highly collaborative Data team and act as a key partner to Product, Engineering, and Commercial teams, using data to shape strategy, improve personalisation, and create a best-in-class experience for millions of users. This role is ideal for someone who is curious, commercially focused, and passionate about understanding user behaviour to drive measurable outcomes \n \n You’ll be responsible for: \n\n • Analysing user behaviour, spotting trends, and telling compelling data stories to influence product strategy\n, • Designing, running, and evaluating experiments to optimise product performance and improve conversion\n, • Defining and aligning key metrics across teams, ensuring consistent measurement and insight delivery\n, • Building and maintaining dashboards and self-serve tools for quick access to core insights\n, • Conducting deep-dive analysis to inform strategic decisions and drive measurable product improvements\n\n \n Your Skills & Experience \n \n I’m looking for someone who is excited to work in a product-focused, consumer-facing environment, and who brings: \n \n\n • Strong SQL\n, • Python/R experience preferrable\n, • Experience with dbt and modern data stacks a bonus\n, • A proven ability to turn data into actionable insights and communicate them clearly to stakeholders\n, • Experience in a B2C or consumer tech environment, ideally with a focus on product analytics or experimentation \n\n \n The Benefits \n \n\n • Salary up to £80,000 – £90,000\n, • Bonus\n\n \n IMPORTANT NOTE \n \n\n • Sponsorship is available for this role\n\n \n How to Apply \n \n Please register your interest by sending your CV to Adam Osborne at Harnham via the Apply link on this page

Senior Scientist – Assay Development (Science Lead) \n London/Stevenage \n Competitive \n \n About the Role \n We are seeking a Senior Scientist – Assay Development to lead the development of next-generation diagnostic assays and provide scientific leadership within an innovative, early-stage health technology business, focused on transforming how we understand women’s hormonal health. \n \n This is a senior, hands-on position with responsibility for defining the assay development strategy, leading scientific decision-making, and driving analytical performance from concept through to validation. You will play a critical role in the development of novel diagnostic technologies, working closely with multidisciplinary teams across engineering, clinical, regulatory, and product development functions. \n \n The role offers a unique opportunity to influence both scientific direction and product development within a growing organisation designed to study dynamic biological systems, not just static snapshots. \n \n What You'll Be Responsible For: \n \n Assay Development & Scientific Leadership \n\n • Lead the design and development of quantitative immunoassays and related diagnostic technologies\n, • Define scientific strategy and development roadmaps\n, • Drive assay optimisation across sensitivity, specificity, precision, reproducibility, and stability\n, • Establish best practice for scientific rigor, experimental design, and data integrity across development activities\n\n \n Method Development & Validation \n\n • Design and execute analytical validation studies\n, • Translate laboratory-based assays into scalable diagnostic formats\n, • Support development of point-of-care, biosensor, microfluidic, or cartridge-based technologies\n, • Ensure scientific activities are supported by robust statistical analysis and data interpretation\n\n \n Regulatory & Quality Documentation \n\n • Author and maintain development, validation, and technical documentation\n, • Ensure documentation meets regulatory and design-control requirements\n, • Maintain traceable and audit-ready scientific records\n, • Support future regulatory submissions and technical file development as required\n\n \n Cross-Functional Collaboration \n\n • Partner closely with engineering, clinical, regulatory, and external collaborators\n, • Support scientific decision-making across product development activities\n, • Identify and engage key scientific advisors and external experts\n, • Contribute technical leadership across strategic projects\n\n \n Team Development \n\n • Help build scientific capability within the business\n, • Mentor and support future scientific hires\n, • Promote a culture of scientific excellence, curiosity, and continuous improvement\n\n \n About You \n\n • A PhD in Biochemistry, Analytical Chemistry, Biomedical Science, Bioengineering, or a related discipline\n, • Extensive industry experience in assay or diagnostic development\n, • Deep hands-on experience developing immunoassays, including ELISA-based technologies\n, • Experience taking assays from concept through validation and ideally towards commercialisation\n, • Strong quantitative, analytical, and statistical skills\n, • Experience working with human biological samples such as blood, saliva, or urine\n, • Excellent scientific communication skills and the ability to explain complex concepts clearly\n, • The ability to work independently and thrive within an entrepreneurial environment\n\n \n Desirable (but not essential): \n\n • Experience with hormone, steroid, or peptide assays\n, • Experience with point-of-care diagnostics, lateral flow, biosensors, or microfluidics\n, • Knowledge of lyophilisation or reagent stabilisation approaches\n, • Familiarity with IVD regulations, design controls, and regulatory submissions\n, • Experience building or leading scientific teams\n, • Experience with machine learning or advanced data analysis approaches\n\n \n Why Join? \n\n • Opportunity to take ownership of a core scientific programme\n, • Significant influence over scientific strategy and product direction\n, • Work on innovative diagnostic technologies with real-world healthcare impact\n, • High degree of autonomy and ownership\n, • Competitive salary and equity participation opportunity\n\n \n Location & Working Pattern \n\n • Based in London\n, • Primarily on-site laboratory-based role\n, • Opportunity to work closely with multidisciplinary technical and product teams\n\n \n The Opportunity \n This is an exceptional opportunity for an experienced assay development scientist to take a leading role within a growing health technology business, helping shape both the science and the product pathway from early-stage innovation through to validated diagnostic solutions. \n \n Apply now by attaching your CV in Word, or contact Paige Keenan (paige.keenan@srgtalent.com) for further information about this opportunity.

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. \n \n This role sits within Elsevier’s Platform Data Science organization, a centralized AI and data science group responsible for advancing intelligent discovery, retrieval, and generative AI capabilities across Elsevier products and platforms. The organization develops foundational AI technologies that power experiences such as LeapSpace, Elsevier’s AI-powered research assistant, as well as Elsevier’s broader Search & AI Platform. \n \n The Platform Data Science organization works at the intersection of: \n\n • Search and retrieval systems\n, • Generative AI and LLM applications\n, • AI evaluation and experimentation\n, • Semantic enrichment and knowledge systems\n, • Scalable AI platforms and intelligent workflows\n\n \n About the role \n We are looking for a Data Scientist III to help design, build, and evaluate advanced AI capabilities supporting LeapSpace and Elsevier’s Search & AI Platform initiatives. This role focuses on applied AI development, retrieval systems, and AI evaluation, helping bring cutting-edge AI technologies into production experiences used by researchers worldwide. \n \n You will work closely with senior data scientists, engineers, product managers, and domain experts across retrieval systems, generative AI, reasoning workflows, evaluation frameworks, and experimentation, contributing to the next generation of AI-powered scientific discovery tools. \n \n This role is ideal for someone with hands-on experience in applied AI, NLP, information retrieval, and LLM-based applications, who enjoys building innovative solutions and translating emerging AI techniques into impactful product capabilities. \n \n Key responsibilities \n Applied AI & Research \n \n\n • Develop and improve LLM-powered research workflows, including:Scientific question answeringLiterature summarizationSemantic exploration and discoveryResearch insight generationCitation-aware retrieval and reasoning workflows\n, • Build and iterate on agentic and multi-step AI workflows using frameworks such as LangGraph and related orchestration tools.\n, • Apply modern techniques in:NLPGenerative AIEmbeddings and semantic representationsRetrieval-augmented generation (RAG)AI reasoning and workflow orchestration\n, • Evaluate emerging AI models, tools, and frameworks and contribute recommendations for experimentation and adoption.\n, • Contribute to prompt engineering, grounding strategies, context management, and hallucination mitigation efforts.\n, • Support integration of scientific metadata, ontologies, and knowledge assets into AI-powered workflows.\n\n \n Search, Retrieval & RAG Systems \n\n • Design, develop, and optimize search and retrieval pipelines, including lexical, vector, and hybrid retrieval approaches.\n, • Contribute to the development and enhancement of RAG systems that integrate LLMs with trusted scientific and biomedical content.\n, • Experiment with embeddings, re-ranking models, chunking strategies, and retrieval orchestration techniques to improve relevance and answer quality.\n, • Support development of semantic search, ranking, and knowledge discovery capabilities.\n, • Collaborate with engineering teams to deploy and scale AI-powered solutions.\n\n \n AI Evaluation & Experimentation \n\n • Develop and apply evaluation frameworks for search and AI systems, including:IR metrics (e.g., NDCG, recall, precision)LLM and RAG evaluation metrics (e.g., grounding, faithfulness, hallucination detection)\n, • Build and maintain evaluation datasets, benchmark suites, and annotation workflows.\n, • Conduct offline experiments and contribute to online experimentation and A/B testing.\n, • Analyze experimental results and communicate findings to stakeholders.\n, • Contribute to responsible AI practices focused on quality, reliability, and trust.\n\n \n Cross-functional Collaboration \n\n • Partner with product managers, engineers, UX researchers, and domain experts to deliver AI-powered capabilities.\n, • Communicate technical findings and recommendations clearly to both technical and non-technical audiences.\n, • Contribute to knowledge sharing and adoption of best practices across the Platform Data Science organization.\n, • Support delivery of projects from research and experimentation through production deployment.\n\n \n Required qualifications \n\n • Batchelor's, Master’s or PhD in Computer Science, Data Science, Machine Learning, NLP, Information Retrieval, or a related field\n, • Experience in data science, machine learning, applied NLP, information retrieval, generative AI, or a related field\n, • Hands-on experience with:LLM-based applications and generative AI systemsRAG pipelines and retrieval systemsSearch and retrieval architectures (lexical, vector, hybrid)Evaluation methodologies for IR and generative AI systems\n, • Strong programming skills in Python\n, • Experience with modern AI/ML frameworks and tooling (e.g., PyTorch, Hugging Face, LangChain, LangGraph, Haystack)\n, • Experience working with Databricks or similar distributed data and machine learning platforms\n, • Understanding of experimentation methodologies, evaluation frameworks, and statistical analysis\n, • Proficiency with data visualization and analytical tooling (e.g., Tableau, Power BI, matplotlib, seaborn)\n, • Demonstrated ability to independently execute technical projects and contribute to cross-functional initiatives\n\n \n Preferred qualifications \n\n • Experience building AI assistants, agentic workflows, or conversational AI applications\n, • Experience working on search, ranking, recommendation, or retrieval systems\n, • Familiarity with scientific, biomedical, or scholarly datasets\n, • Experience with knowledge graphs, ontologies, or semantic enrichment systems\n, • Exposure to production ML systems and MLOps practices\n, • Academic or industry research experience in NLP, information retrieval, search, or generative AI\n, • Experience working in content-rich, knowledge-intensive, or highly regulated domains\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 • Comprehensive Pension Plan\n, • Home, office, or commuting allowance.\n, • Generous vacation entitlement and option for sabbatical leave\n, • Maternity, Paternity, Adoption and Family Care leave\n, • Flexible working hours\n, • Personal Choice budget\n, • Internal communities and networks\n, • Various employee discounts\n, • Recruitment introduction reward\n, • Employee Assistance Program (global)\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. \n

Senior Data Scientist \n £70,000–£80,000 + £5,000 Car Allowance + Bonus \n London(Hybrid – 2x Days a Week in Office) \n \n If you enjoy solving complex modelling problems, building innovative machine learning solutions, and working with alternative data to challenge traditional pricing strategies, this is an opportunity to join one of the UK's strongest data science functions! \n \n The Company \n \n This leading UK financial services business has built one of the most mature data science capabilities in the industry, using advanced analytics and machine learning to drive commercial decision-making across millions of customers; with significant investment in technology, data and AI, the business continues to grow rapidly and is looking to expand its Alternative Pricing Product team with a Senior Data Scientist. You'll join a highly collaborative environment where experimentation is encouraged and innovative modelling techniques are actively deployed into production! \n \n The Role \n \n Reporting into the Head of Pricing, you'll join a specialist team responsible for developing next-generation pricing models that challenge conventional approaches. Working across large and complex datasets, you'll build predictive machine learning models using alternative data sources to improve customer pricing and risk selection. \n \n Projects include: \n\n • Building innovative predictive machine learning models\n, • Developing pricing and customer selection models\n, • Exploring alternative data sources to improve pricing accuracy\n, • Geospatial and footprint modelling\n, • Residual and claims modelling\n, • Working with messy, high-volume datasets to uncover commercial insights\n, • Deploying models using Azure Machine Learning\n, • Mentoring junior team members and helping shape best practice across the team\n\n \n This is an opportunity to influence products that impact millions of customers whilst working on genuinely novel modelling challenges. \n \n Your Skills & Experience \n \n\n • Experience building machine learning models\n, • Strong Python skills\n, • Experience developing predictive models within commercial environments\n, • Experience working with large, complex datasets\n, • Experience with cloud-based ML platforms (Azure ML preferred)\n, • The ability to communicate technical findings to non-technical stakeholders\n, • Experience mentoring or supporting more junior data scientists is advantageous\n\n \n Experience within insurance or financial services would be beneficial, although candidates from other highly analytical industries are also encouraged to apply. \n \n The Benefits \n \n\n • £70,000–£80,000 salary\n, • £5,000 annual car allowance\n, • Bonus\n\n \n How to Apply \n \n To register your interest in this opportunity, please send your CV via the application link

Research Physics Expert \n \n Location: Remote \n \n Engagement Type: Hourly Contract \n \n Compensation: $61–$77/hour \n \n About the Opportunity \n This opportunity is for experienced Physics Researchers interested in contributing to advanced AI research and evaluation projects. You will help develop and validate high-quality reference solutions for frontier-level physics benchmarks, ensuring that next-generation AI systems are evaluated against rigorous scientific standards. \n The work involves solving complex research-level physics problems, reviewing expert solutions, and contributing to the creation of human-verified benchmark data used to measure AI reasoning capabilities. \n Ideal Qualifications \n • PhD, Postdoctoral Researcher, Faculty Member, or Industry Research Scientist in Physics or a related field. \n • Expertise in one or more areas including High Energy Physics, Mathematical Physics, Biophysics, Statistical Physics, Condensed Matter Physics, AMO Physics, Cosmology, Astrophysics, Quantum Information, or Quantum Mechanics. \n • Strong publication record demonstrating research expertise in a relevant subfield. \n • Experience solving complex research-level physics problems and developing rigorous scientific analyses. \n • Proficiency with Python, Jupyter Notebooks, SymPy, and LaTeX. \n • Excellent analytical reasoning, problem-solving, and scientific communication skills. \n • Strong attention to detail and commitment to scientific accuracy. \n Responsibilities \n • Solve research-level physics problems and develop complete reference solutions. \n • Create structured problem decompositions and verification methodologies. \n • Author Python-based answer templates and automated validation functions. \n • Review and audit submitted solutions for correctness, rigor, and methodological soundness. \n • Provide detailed feedback to improve solution quality and benchmark reliability. \n • Adjudicate between competing solution approaches and determine final reference answers. \n • Document derivations, verification procedures, error tolerances, and scientific rationale. \n • Contribute to the development of high-quality benchmark datasets for evaluating frontier AI systems. \n Project Details \n • Expected commitment of approximately 10 hours per week. \n • Fully remote and asynchronous work environment. \n • Opportunity to collaborate with leading AI researchers and domain experts. \n • Long-term project engagement with potential extensions based on project needs. \n Compensation \n • Competitive compensation of $80–$135/hour. \n • Weekly payments. \n • Independent contractor engagement. \n Application Process \n\n • Submit your resume, publication record, or research background.\n, • Complete any required assessment or evaluation.\n, • Participate in the expert review process.\n, • Final selection and onboarding.\n\n

I'm currently supporting a global biopharmaceutical organisation in their search for an experienced Principal Scientist to join a highly collaborative quantitative sciences team. \n This role offers the opportunity to influence project strategy from early research through to clinical development, applying translational modelling and simulation approaches to support key drug development decisions. \n Key Responsibilities: \n\n • Lead quantitative pharmacology and translational modelling strategies across a diverse project portfolio.\n, • Integrate preclinical and translational data to inform decision-making and support progression into clinical development.\n, • Develop mechanistic and PK/PD models to evaluate hypotheses, optimise study design, and support strategic development plans.\n, • Collaborate with multidisciplinary teams across areas such as translational medicine, safety sciences, bioanalysis, and clinical development.\n, • Provide scientific leadership on modelling and simulation activities both internally and through external partnerships.\n, • Contribute to regulatory documentation and strategic submissions where required.\n\n What We're Looking For: \n\n • PhD in Systems Biology, Pharmacometrics, PK/PD, or a related discipline.\n, • Strong experience applying modelling and simulation approaches within drug discovery and development.\n, • Demonstrated ability to design and execute quantitative pharmacology strategies spanning research through early clinical development.\n, • Experience working within complex, matrixed R&D environments.\n, • Proficiency with modelling tools such as R, Monolix, Phoenix, or similar platforms.\n, • Excellent communication skills, with the ability to influence stakeholders across scientific disciplines.\n\n Why Consider This Opportunity? \n\n • High-profile role with significant scientific impact.\n, • Exposure to innovative therapeutic programmes.\n, • Strong emphasis on collaboration, innovation, and translational science.\n, • Opportunity to shape strategy and contribute to the advancement of novel medicines.\n\n \n \n

Senior/Principal Machine Learning Scientist (Generative Modelling) \n \n About Relation \n Relation is a sector defining TechBio company developing transformational medicines, with technology at our core. Our ambition is to understand human biology in unprecedented ways, discovering therapies to treat some of life’s most devastating diseases. We leverage single-cell multi-omics from patient tissue, functional assays, and machine learning to drive disease understanding, from cause to cure. \n We are scaling rapidly and building a team of exceptional individuals to push the boundaries of drug discovery. You will work in highly interdisciplinary teams where biology, computation, and engineering come together to solve complex problems that have not been solved before. Our state-of-the-art wet and dry labs in the heart of London are designed to accelerate this integration and translate insight into impact. \n We are committed to building diverse and inclusive teams. Relation is an equal opportunities employer and does not discriminate on the basis of gender, sexual orientation, marital or civil partnership status, gender reassignment, race, colour, nationality, ethnic or national origin, religion or belief, disability, or age. \n By joining Relation, you will help define how medicines are discovered and deliver meaningful impact for patients. \n \n The opportunity \n Relation is offering an outstanding opportunity for a Machine Learning Scientist to help build the next generation of generative and predictive models of cellular behaviour. Your work will be central to our mission to understand and control cellular decision-making, enabling novel therapeutic strategies grounded in generative models. \n You'll be joining a team with access to cutting-edge multiomic and interventional datasets, advanced computational infrastructure, and deep interdisciplinary expertise. We embrace modern ML tooling, including agentic workflows, to accelerate the pace of research iteration. This is an opportunity to push the boundaries of what generative modelling can achieve in complex, high-dimensional, and noisy real-world systems, and to see your work tested directly in experimental biology. \n \n Day to day, you will \n\n • Design and implement generative modelling approaches that learn intervention effects from diverse biological data, including single-cell perturbation experiments.\n, • Develop models that go beyond correlation, focusing on generalisation, counterfactual prediction, and experimental design.\n, • Collaborate with experimental teams to design and validate computational hypotheses via iterative strategies that identify the highest-signal next experiment.\n, • Evaluate models not just for fit, but for causal coherence, mechanistic fidelity, and utility in guiding real-world interventions.\n, • Communicate findings clearly to colleagues and stakeholders from different disciplines.\n\n \n Professionally, you will have \n\n • PhD in ML, statistics, computer science, or a related quantitative field.\n, • Deep expertise in generative modelling.\n, • Strong foundations in probabilistic modelling, representation learning, or neural network architectures for structured or sequential data.\n, • Excellence in Python and familiarity with scalable ML tooling and high-performance computing.\n, • A disciplined approach to model evaluation, with experience designing experiments that go beyond standard benchmarks to test real-world utility.\n, • Willingness and ability to engage deeply with biological data; prior experience with single-cell or perturbational datasets is a strong plus.\n\n Bonus experience: \n\n • Track record of impactful publications or open-source contributions in ML.\n, • Experience working in interdisciplinary teams or applying ML in real-world settings.\n\n \n Personally, you \n\n • Are comfortable working in a matrixed environment, balancing multiple stakeholders and contributing effectively across teams.\n, • Take ownership of your work, proactively seek opportunities to contribute, and enable others to do their best work.\n, • Communicate openly and directly, give and receive feedback constructively, and handle challenging conversations with respect.\n, • Actively seek out diverse perspectives, build strong working relationships, and contribute to shared goals across teams.\n, • Embrace challenges with openness and resilience, set high standards for yourself, and strive to deliver meaningful outcomes.\n\n \n Working Style & Culture at Relation \n At Relation, we operate in a matrixed, interdisciplinary environment, where impact is driven through collaboration across scientific, technical, and operational domains. We collaborate, and you will partner with colleagues across multiple teams and projects, contributing your expertise while aligning to shared company priorities. We work together and win together! The patient is waiting! \n \n Recruitment Agencies \n Please note that Relation does not accept unsolicited resumes from agencies. Resumes should not be forwarded to our job aliases or employees. Relation will not be liable for any fees associated with unsolicited CVs. \n

Senior Bioinformatics Scientist (Genomic Foundation Models) \n \n London (Hybrid) | Up to £130,000 + Equity | Some flexibility for exceptional candidates \n \n We're partnering with a London-based BioAI company that is doing something genuinely rare. \n \n Backed by one of the world's leading AI infrastructure companies and working alongside frontier AI partners, they've built the largest proprietary biological dataset on the planet, spanning billions of genes across millions of species. Following a recent Series B, they're using that data to train genomic and protein foundation models capable of designing entirely novel biological systems. \n \n Their ambition is to compress decades of biological discovery into years. The dataset they're training on doesn't exist anywhere else, which means the modelling opportunities here are unlike anything available in academia or at other companies working off public data. \n \n The Role \n You'll sit at the centre of their foundation model efforts, shaping the data strategy behind their genomic and protein models. You'll be deciding what data the models need, curating and evaluating training datasets, fine-tuning models for real biological applications, and working directly with ML engineers and biologists to translate biological questions into model objectives. \n \n Requirements \n\n • You have built novel deep learning architectures or frameworks applied to genomics or protein modelling. This is the defining requirement for this role. We're looking for people who design and implement models, not solely use or fine-tune existing ones.\n, • Hands-on experience with Transformer-based or foundation model architectures in a biological context (e.g. Enformer, Nucleotide Transformer, Evo, HyenaDNA, ESM, or comparable)\n, • Understanding of regulatory genomics, non-coding variant prediction, or gene regulation at a level where you can make modelling decisions informed by the biology\n, • Experience curating or evaluating training data for large-scale biological models\n, • Deep learning must be a core competency, not a secondary skill. Strong biology alone is not sufficient, and general ML experience without biological applications won't translate.\n\n \n Strong Preferences \n\n • Published work applying deep learning to functional genomics or variant effect prediction\n, • Experience with protein language models (ProGen, ESMFold, or similar)\n, • Familiarity with models like DeepSEA, Sei, Basenji, BPNet, ChromBPNet, SpliceAI, or AlphaGenome\n\n

Drug Discovery Scientist \n \n Position: Drug Discovery Scientist \n \n Type: Hourly Contract \n \n Compensation: $60–$90/hour \n \n Location: Remote \n \n About the Opportunity \n This opportunity is for experienced Drug Discovery Scientists to contribute to an advanced AI research and evaluation project focused on pharmaceutical research and development. \n You'll apply your scientific expertise to design realistic, evidence-driven drug discovery problems that require AI models to reason through incomplete, indirect, and potentially misleading scientific evidence. You'll create research prompts, build supporting data rooms using real source-grounded information, develop rigorous grading frameworks, and validate the resulting tasks. \n The role is ideal for experts who can distinguish genuine scientific reasoning from pattern matching and confidently evaluate the quality of complex research conclusions. \n Responsibilities \n\n • Design challenging, realistic drug discovery research problems based on authentic scientific workflows.\n, • Develop research scenarios where the correct conclusion must be derived from multiple pieces of evidence rather than directly stated.\n, • Build comprehensive data rooms using real, source-grounded scientific data and documentation.\n, • Ensure every decisive scientific value and piece of evidence can be traced back to a reliable source.\n, • Create detailed grading documents and evaluation rubrics that assess scientific reasoning and substantive conclusions.\n, • Evaluate AI-generated research outputs for scientific accuracy, logical consistency, and defensibility.\n, • Run verification and calibration processes to ensure tasks are reproducible, appropriately difficult, and objectively scorable.\n, • Identify weaknesses in task design, evidence, or evaluation criteria and revise them accordingly.\n, • Provide expert judgment on scientific questions, task difficulty, and the quality of AI reasoning.\n, • Collaborate with project reviewers and other domain experts to refine research tasks.\n\n Required Qualifications \n\n • Professional expertise in one or more of the following areas:\n, • Mechanistic enzymology\n, • Structure-guided peptide design\n, • Structure-guided antibody design\n, • Fragment-based drug discovery\n, • Structure-based medicinal chemistry\n, • PhD or equivalent industry experience in drug discovery, medicinal chemistry, chemical biology, biochemistry, or a closely related field.\n, • Strong understanding of drug discovery research methodologies and scientific evidence evaluation.\n, • Ability to construct complex scientific problems with defensible conclusions.\n, • Strong analytical and critical-thinking skills.\n, • Ability to evaluate scientific reasoning quality, not simply final answers.\n, • Strong scientific writing and documentation skills.\n, • Comfortable working independently in a remote research environment.\n, • Ability to commit at least 20 hours per week.\n\n Preferred Qualifications \n\n • Experience designing or evaluating drug discovery research strategies.\n, • Strong background in structure-based drug design, protein–ligand interactions, enzymology, or molecular discovery.\n, • Experience working with scientific literature, experimental datasets, structural data, and research documentation.\n, • Experience developing research assessments, scientific benchmarks, or evaluation frameworks.\n, • Familiarity with open-source scientific tooling and computational research workflows.\n, • Experience evaluating AI-generated scientific research or technical outputs is a plus.\n, • Strong ability to distinguish defensible scientific conclusions from unsupported assumptions or superficial reasoning.\n\n Compensation \n\n • Competitive compensation of $60–$90/hour.\n, • Hourly contract engagement.\n, • Fully remote.\n, • Minimum commitment: 20 hours/week.\n, • Up to 40 hours/week available.\n, • Claude Max subscription required for the project and fully reimbursed.\n, • Work conducted through a browser-based research studio and Claude Code.\n\n Application Process \n\n • Apply to the role\n, • Complete the required screening questions\n, • Provide details about your drug discovery and scientific research experience\n, • Complete the relevant scientific assessment\n, • Participate in the evaluation/interview stage\n, • Complete onboarding and tooling setup\n, • Begin designing and evaluating drug discovery research tasks\n\n

Drug Discovery Scientist \n \n Position: Drug Discovery Scientist \n \n Type: Hourly Contract \n \n Compensation: $60–$90/hour \n \n Location: Remote \n \n About the Opportunity \n This opportunity is for experienced Drug Discovery Scientists to contribute to an advanced AI research and evaluation project focused on pharmaceutical research and development. \n You'll apply your scientific expertise to design realistic, evidence-driven drug discovery problems that require AI models to reason through incomplete, indirect, and potentially misleading scientific evidence. You'll create research prompts, build supporting data rooms using real source-grounded information, develop rigorous grading frameworks, and validate the resulting tasks. \n The role is ideal for experts who can distinguish genuine scientific reasoning from pattern matching and confidently evaluate the quality of complex research conclusions. \n Responsibilities \n\n • Design challenging, realistic drug discovery research problems based on authentic scientific workflows.\n, • Develop research scenarios where the correct conclusion must be derived from multiple pieces of evidence rather than directly stated.\n, • Build comprehensive data rooms using real, source-grounded scientific data and documentation.\n, • Ensure every decisive scientific value and piece of evidence can be traced back to a reliable source.\n, • Create detailed grading documents and evaluation rubrics that assess scientific reasoning and substantive conclusions.\n, • Evaluate AI-generated research outputs for scientific accuracy, logical consistency, and defensibility.\n, • Run verification and calibration processes to ensure tasks are reproducible, appropriately difficult, and objectively scorable.\n, • Identify weaknesses in task design, evidence, or evaluation criteria and revise them accordingly.\n, • Provide expert judgment on scientific questions, task difficulty, and the quality of AI reasoning.\n, • Collaborate with project reviewers and other domain experts to refine research tasks.\n\n Required Qualifications \n\n • Professional expertise in one or more of the following areas:\n, • Mechanistic enzymology\n, • Structure-guided peptide design\n, • Structure-guided antibody design\n, • Fragment-based drug discovery\n, • Structure-based medicinal chemistry\n, • PhD or equivalent industry experience in drug discovery, medicinal chemistry, chemical biology, biochemistry, or a closely related field.\n, • Strong understanding of drug discovery research methodologies and scientific evidence evaluation.\n, • Ability to construct complex scientific problems with defensible conclusions.\n, • Strong analytical and critical-thinking skills.\n, • Ability to evaluate scientific reasoning quality, not simply final answers.\n, • Strong scientific writing and documentation skills.\n, • Comfortable working independently in a remote research environment.\n, • Ability to commit at least 20 hours per week.\n\n Preferred Qualifications \n\n • Experience designing or evaluating drug discovery research strategies.\n, • Strong background in structure-based drug design, protein–ligand interactions, enzymology, or molecular discovery.\n, • Experience working with scientific literature, experimental datasets, structural data, and research documentation.\n, • Experience developing research assessments, scientific benchmarks, or evaluation frameworks.\n, • Familiarity with open-source scientific tooling and computational research workflows.\n, • Experience evaluating AI-generated scientific research or technical outputs is a plus.\n, • Strong ability to distinguish defensible scientific conclusions from unsupported assumptions or superficial reasoning.\n\n Compensation \n\n • Competitive compensation of $60–$90/hour.\n, • Hourly contract engagement.\n, • Fully remote.\n, • Minimum commitment: 20 hours/week.\n, • Up to 40 hours/week available.\n, • Claude Max subscription required for the project and fully reimbursed.\n, • Work conducted through a browser-based research studio and Claude Code.\n\n Application Process \n\n • Apply to the role\n, • Complete the required screening questions\n, • Provide details about your drug discovery and scientific research experience\n, • Complete the relevant scientific assessment\n, • Participate in the evaluation/interview stage\n, • Complete onboarding and tooling setup\n, • Begin designing and evaluating drug discovery research tasks\n\n

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.

Senior Data Scientist (Single Cell) \n \n About Relation \n Relation is a sector defining TechBio company developing transformational medicines, with technology at our core. Our ambition is to understand human biology in unprecedented ways, discovering therapies to treat some of life’s most devastating diseases. We leverage single-cell multi-omics from patient tissue, functional assays, and machine learning to drive disease understanding, from cause to cure. \n We are scaling rapidly and building a team of exceptional individuals to push the boundaries of drug discovery. You will work in highly interdisciplinary teams where biology, computation, and engineering come together to solve complex problems that have not been solved before. Our state-of-the-art wet and dry labs in the heart of London are designed to accelerate this integration and translate insight into impact. \n We are committed to building diverse and inclusive teams. Relation is an equal opportunities employer and does not discriminate on the basis of gender, sexual orientation, marital or civil partnership status, gender reassignment, race, colour, nationality, ethnic or national origin, religion or belief, disability, or age. \n By joining Relation, you will help define how medicines are discovered and deliver meaningful impact for patients. \n \n The opportunity \n Relation is offering an outstanding opportunity for a Senior Data Scientist to help build the next generation of generative and predictive models of cellular behaviour, with a focus on single cell multi-omics. Your work will be central to our mission to understand and control cellular decision-making, enabling novel therapeutic strategies grounded in generative models. \n You'll be joining a team with access to cutting-edge multiomic and interventional datasets, advanced computational infrastructure, and deep interdisciplinary expertise, and a culture that embraces modern ML tooling, including agentic workflows, to accelerate research iteration. You will contribute advanced data analysis and domain expertise to challenge ML models that aim to predict and explain cellular decision-making in disease. \n \n Day to day, you will \n\n • Process and QC paired single-cell RNA-seq and scATAC-seq at scale from thousands of perturbations across diverse cell types and biological contexts.\n, • Develop and maintain Nextflow pipelines compatible with custom combinatorial indexing chemistries and including methods such as STARsolo, Alevin-fry, Chromap, and SnapATAC2.\n, • Integrate scRNA-seq and scATAC-seq with extracellular proteomics and high-content imaging to build multimodal training datasets.\n, • Manage data in memory-efficient formats (e.g. Zarr) for GPU-accelerated processing and model training at scale.\n, • Partner closely with wet lab scientists from screen and cohort design through to interpretation, so experiments are analytically tractable and pipelines maximise data value.\n, • Contribute to the evaluation framework that determines whether ML models capture meaningful biology: design metrics, held-out benchmarks, and biological sanity checks.\n, • Collaborate closely with ML modellers to develop model architectures.\n, • Present findings and methodologies to internal stakeholders and contribute to publications.\n\n \n Professionally, you will have \n\n • A PhD (or equivalent industry experience) in computational biology, bioinformatics, or a related quantitative field.\n, • Deep hands-on experience processing and analysing large-scale single-cell multiomics data, ideally including paired RNA + ATAC (10x Multiome or equivalent).\n, • Proficiency with single-cell analysis toolkits (e.g. scverse ecosystem) and workflow management frameworks (Nextflow, Snakemake).\n, • Experience with arrayed CRISPR perturbation screen data, including well-level perturbation assignment via sample hashing, perturbation-specific QC (e.g. MOI estimation), and single-cell effect quantification.\n, • Proficiency in Python and familiarity with high-performance computing environments.\n, • Strong communication skills to bridge experimental and ML teams across a fast-moving programme\n\n Bonus Experience: \n\n • Experience integrating multiple data modalities (transcriptomics, chromatin accessibility, imaging and proteomics) for joint analysis.\n, • Exposure to foundation model development or perturbation prediction models.\n, • A background in statistical modelling and algorithm development.\n, • Experience working in interdisciplinary teams.\n\n \n Personally, you \n\n • Are comfortable working in a matrixed environment, balancing multiple stakeholders and contributing effectively across teams.\n, • Take ownership of your work, proactively seek opportunities to contribute, and enable others to do their best work.\n, • Communicate openly and directly, give and receive feedback constructively, and handle challenging conversations with respect.\n, • Actively seek out diverse perspectives, build strong working relationships, and contribute to shared goals across teams.\n, • Embrace challenges with openness and resilience, set high standards for yourself, and strive to deliver meaningful outcomes.\n\n \n Working Style & Culture at Relation \n At Relation, we operate in a matrixed, interdisciplinary environment, where impact is driven through collaboration across scientific, technical, and operational domains. We collaborate, and you will partner with colleagues across multiple teams and projects, contributing your expertise while aligning to shared company priorities. We work together and win together! The patient is waiting! \n \n Recruitment Agencies \n Please note that Relation does not accept unsolicited resumes from agencies. Resumes should not be forwarded to our job aliases or employees. Relation will not be liable for any fees associated with unsolicited CVs.

(Senior) Research Scientist for in vivo work \n \n Location: Navira Ltd, at the Francis Crick Institute, London NW1 (on site) Closing date: 30 Sep 2026 Start date: Flexible; priority for early joiners Salary: £40,000–£55,000 depending on experience Contact: careers@navira.bio \n \n About Navira \n Navira is a spin-out of the Francis Crick Institute developing the next generation of AAV-based delivery systems. Our engineered AAV capsids are built to solve the problem that limits most CNS gene therapies: getting vectors across the blood-brain barrier, into the right cells, at a dose that is safe. We are a team of 6 scientists working out of lab space at the Crick, with a multi-year programme funded by a UK government body and venture funding. We combine capsid engineering, protein design and in vivo validation, which means the person doing the animal work sits at the centre of the programme rather than at the end of it. \n \n The Role \n We are seeking a passionate and enthusiastic (Senior) Research Scientist to join our team to accelerate the validation of our vector designs in vivo. \n In this role, you will contribute to assessing the performance and refinement of Navira’s AAV platforms in vivo using mice, in the spirit of the 3Rs of animal research. As such, you will be part of the team responsible for the pre-clinical validation of our delivery systems, with particular focus on applications to neurological conditions. These experiments are pivotal to the success of our research programme and therefore you will be highly involved in the activities performed by the entire team. \n The position is based at our research laboratory within the Francis Crick Institute in central London (NW1), near King’s Cross, where the work will be carried out in person. If you’re excited about advancing gene therapies and their impact, we’d love to hear from you! \n \n Key responsibilities \n\n • Work collaboratively with your colleagues to ensure effective coordination\n, • Design and write study plans for experiments autonomously\n, • Perform regulated procedures on animal models in compliance with the relevant regulatory framework\n, • Maintain a high-quality record of all experiments performed\n, • Report and present research findings and developments including status and results clearly and efficiently both internally and externally, verbally and in writing, in a fast paced environment.\n\n \n About you \n Essential \n\n • A current Home Office Procedural Individual Licence (PIL A/B/C)\n, • Experience with stereotactic intracranial and IV injections\n, • Confidence in animal handling\n, • Ability to independently troubleshoot and implement research projects\n, • Strong organisational and record-keeping skills\n, • Comfortable working in a fast-moving start-up research environment\n, • Ability to work on a team-based project with experimental researchers\n, • Proficiency in efficient time management\n, • Ability to deliver work within the necessary timelines\n\n \n Desirable (but not required) \n\n • Neuroscience background and/or experience\n, • Experience with the use of viral vectors, such as AAV\n, • Experience with tissue processing for protein/RNA/DNA quantification\n, • Experience with Bioluminescence Imaging (BLI)\n, • Experience with pre-clinical disease models\n, • Experience with cell culture and AAV production\n\n \n What benefits Navira has to offer \n\n • A central role in a small team, where your data decides which candidates advance\n, • Secured multi-year programme funding, so the R&D has runway\n, • A competitive salary and equity options, depending on experience\n, • Generous Pension and private health insurance\n, • Lab space at the Francis Crick Institute in central London, with canteen and on-site facilities\n, • Cycle to work scheme and secure bike storage\n\n \n All offers are subject to successful security screening and continuous eligibility to work in the United Kingdom. We are not able to sponsor visa applications for this role. \n \n Application closes: 30 September 2026 \n Role Start date: Flexible, starting as soon as possible, priority for early joiners. \n Contact: Karl Brune, careers@navira.bio \n \n Statement \n At Navira, we embrace and celebrate the diversity of experiences, knowledge, backgrounds, and perspectives, recognizing their power to drive extraordinary impact. We are dedicated to providing equal employment opportunities to all, regardless of sex, race, religion, beliefs, ethnic or national origin, disability, age, citizenship, marital, domestic, or civil partnership status, sexual orientation, gender identity, pregnancy, breastfeeding, or any other characteristic protected by applicable law. If you have a disability or additional need that requires accommodation, please do not hesitate to let us know. \n \n Privacy Notice

Data Product Manager | Decisioning \n \n 📍 London: 1-2 days per week in the office \n 💵 £100,000-£114,000 + bonus \n \n Are you a Product Manager who wants to sit at the intersection of data science, personalisation and commercial strategy, with real influence over how a business makes decisions at scale? \n \n If so, this could be the ideal next step for you. \n \n As Data Product Manager, you'll wrap around the data science team and own the experimentation paradigm, helping shape the decisioning and personalisation strategy - next best action, next best offer, recommender systems - for a large consumer loyalty business with a genuinely rich and complex data ecosystem. You'll prioritise the DS roadmap, align data science output with front-end product teams, and make sure the team is working on the highest-value bets rather than technically impressive but strategically misaligned ones. This role exists precisely because that alignment gap is real: a fully functional semantic search product was built without front-end buy-in and still isn't in use. \n \n What are they looking for? \n\n • A former data scientist who has moved into product, or equivalent experience turning data science and optimisation work into real products\n, • Someone who has worked inside a data science function and understands how models actually get built\n, • Strong product judgement, able to weigh up model development by business impact rather than technical polish alone\n, • Comfortable holding your own with data scientists on what's feasible and what trade-offs are worth making\n, • Confidence operating with senior stakeholders, including where priorities genuinely conflict\n, • A solid grasp of how data science and experimentation work is typically structured and delivered\n, • A track record of getting models out of testing and into everyday use, not just building something clever\n\n \n What's in it for you? \n\n • A rare product role that sits genuinely at the intersection of data science, personalisation and commercial strategy\n, • Real influence over how decisioning and personalisation work end-to-end, not just at the margins\n, • A business with a rich, complex data ecosystem and real scale to make an impact in\n, • A mandate to fix a known problem - misalignment between DS output and front-end delivery - rather than inherit a vague brief\n\n \n Please get in touch now for more information on both the role and the company!

Are you motivated to build scalable data solutions that directly shape customer engagement and marketing performance? \n \n Do you enjoy collaborating across teams to turn complex data into actionable insights and real-time decision making? \n \n \n About the Business \n LexisNexis® Risk Solutions provides customers with solutions and decision tools that combine public and industry-specific content with advanced technology and analytics to assist in evaluating and predicting risk and enhancing operational efficiency. \n We use the power of data and advanced analytics to help our customers make better, timelier decisions. By bringing clarity to information, we help make communities safer, insurance rates more accurate, commerce more transparent, business decisions easier, and processes more efficient. \n \n About Our Team \n The MarTech – Marketing Automation team is a dynamic group managing several SaaS-based solutions within the Marketing Technology stack for LNRS Data Services. \n \n About the Role \n This role focuses on building and optimising data infrastructure that enables advanced marketing and customer data capabilities. You will create scalable pipelines, data models, and governance practices that support analytics, segmentation, and real-time engagement. Working closely with cross-functional teams, you will help deliver reliable, high-quality data solutions that drive business outcomes. \n \n Responsibilities \n\n • Build and maintain scalable data pipelines integrating customer, campaign, and operational data into the CDP and marketing data layer\n, • Design and manage data models to support segmentation, lifecycle analytics, attribution, and KPI measurement\n, • Ensure data quality, consistency, deduplication, and optimisation for analytics and reporting use cases\n, • Enable CDP functionality including identity resolution, consent management, and audience readiness\n, • Develop event streams and triggers to support customer journey orchestration and real-time decisioning\n, • Provide structured datasets and semantic layers for dashboards and advanced analytics\n, • Implement data governance practices, including lineage, cataloguing, validation, and GDPR/PII compliance\n, • Partner with analytics, MarTech, and marketing teams to align data solutions with business needs\n\n \n \n Requirements \n\n • Strong SQL skills and experience with ETL/ELT and pipeline orchestration tools (e.g., Airflow, dbt, Data Factory)\n, • Experience with cloud data platforms (e.g., Azure, AWS, or GCP)\n, • Proficiency in data modelling (dimensional, entity-relationship, event-driven)\n, • Understanding of marketing data ecosystems, including CDPs, CRM, and behavioural data\n, • Experience supporting analytics and BI tools (e.g., Power BI, Tableau) from a data engineering perspective\n, • Knowledge of data governance, quality frameworks, and secure data handling (including GDPR/PII)\n, • Ability to translate business requirements into scalable technical solutions\n, • Strong collaboration and communication skills with technical and non-technical stakeholders\n\n \n You can learn more about LexisNexis Risk Solutions here: \n LexisNexis Risk Solutions

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.

Lead Consultant (Consumer AI & Data Science) \n London Based | £80k - £100k + Bonus + Benefits | Travel Required \n \n If you enjoy solving complex commercial problems with AI, machine learning and advanced analytics, this is an opportunity to work on high-impact transformation programmes where your solutions are implemented, measured and scaled. \n \n Joining a growing digital capability within a specialist consultancy, you'll work at the intersection of data science, AI and strategy, helping some of the largest consumer brands improve customer experiences, optimise operations and unlock measurable business value. \n \n The Company \n They are a well-established consultancy known for delivering tangible business outcomes across complex transformation programmes. Their digital and AI capability is growing rapidly, creating an opportunity for experienced consultants to have a significant influence on both client delivery and the future direction of the practice. \n \n The business invests heavily in learning, development and progression, providing clear pathways for individuals who want to combine technical expertise with consulting and leadership responsibilities. \n \n The Role \n As a Lead Consultant, you will work directly with consumer-focused clients to identify opportunities where AI, machine learning and advanced analytics can create commercial value. \n You will: \n\n • Lead AI, machine learning and data science workstreams from concept through to implementation\n, • Identify opportunities to improve customer experience, personalisation and commercial performance\n, • Design and deliver data-driven solutions that move beyond proof of concept into operational use\n, • Advise senior client stakeholders on digital strategy and emerging technologies\n, • Translate technical concepts into clear business recommendations\n, • Lead multidisciplinary teams across data, technology and business functions\n, • Mentor and develop junior consultants and team members\n, • Support business growth through solution design and client engagement\n\n \n Your Skills & Experience \n\n • Strong commercial experience within Data Science, Machine Learning, AI or Advanced Analytics\n, • Experience delivering projects within consulting, professional services or a client-facing environment\n, • Proven track record of delivering measurable business impact\n, • Ability to shape solutions as well as execute delivery\n, • Excellent stakeholder management and communication skills\n, • Experience working with consumer, retail, e-commerce, customer or digital products\n, • Exposure to Generative AI, LLMs or modern AI tooling\n, • Passion for mentoring others and building capability\n\n \n What They Offer \n\n • Up to £100k base salary and performance-based bonus\n, • Profit share and long-term incentive opportunities\n, • Clear progression pathway from Lead through to senior leadership\n, • Dedicated career development support and mentoring\n, • Exposure to a wide range of AI, machine learning and analytics challenges\n, • Opportunity to work with senior client stakeholders and executive teams\n, • Comprehensive benefits package including pension, life assurance and wellbeing support\n\n \n How to Apply \n If you're looking for a consultancy role where you can combine AI expertise, client engagement and real business impact, apply today to learn more.

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.

Senior Data Scientist \n \n Location – London – Hybrid \n \n Salary - £75k – £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 \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 Experience in consultancy or client-facing environments would be advantageous but isn't essential. \n If you're motivated by technically challenging work, enjoy solving problems with no obvious answer, and want to see your expertise applied where it has genuine impact, you'll find plenty to get excited about here. \n \n \n Interested? Then let’s talk!

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

Research Scientist \n \n The role will focus on the development and execution of in vivo potency assays and safety studies, with particular emphasis on CNS/neuroscience and ocular/retinal research. \n \n Key Responsibilities \n\n • Design, develop and execute in vivo gene therapy potency and safety studies.\n, • Support gene therapy programmes from early discovery through to clinical development.\n, • Develop and optimise AAV-based therapeutic assays and readouts.\n, • Work with multidisciplinary R&D, quality and compliance teams.\n, • Develop and improve laboratory processes, workflows and technologies.\n, • Design and write SOPs, work instructions and experimental protocols.\n, • Support technology transfer and implementation of process improvements.\n, • Contribute to the development of a growing R&D laboratory facility.\n, • Deliver experiments within agreed timelines, budgets and quality standards.\n\n \n Essential Experience \n\n • Degree-level qualification in a biological science; MSc/PhD preferred\n, • Strong experience in molecular biology, including techniques such as DNA/RNA extraction, dPCR and Western blotting.\n, • Proven in vivo research experience within CNS/neuroscience, brain or retinal/ocular models.\n, • Experience with AAV-based gene therapy and relevant therapeutic readouts.\n, • Experience with histology, including cryosectioning and immunohistochemistry.\n, • Strong understanding of experimental design and process development/validation.\n, • Experience developing, evaluating and implementing new techniques or technologies.\n, • Experience working with small animal models; previous/current Home Office personal licence experience would be advantageous.\n, • Ability to work effectively in a multidisciplinary, controlled research environment.\n\n \n The Ideal Candidate \n We are looking for a scientist who combines strong hands-on molecular biology and in vivo expertise with the ability to develop assays, troubleshoot experiments and improve existing processes. \n \n You should be comfortable working independently, managing experimental timelines and budgets, and communicating scientific findings clearly to both technical and non-technical colleagues.

\n Senior Data Scientist, Graph Risk Analytics\n Department: Engineering \n Employment Type: Full Time \n Location: London \n Compensation: £105,000 - £120,000 / year Description\n Location: London, UK \n Annual Remuneration: £105,000 - £120,000 and discretionary annual bonus \n Pay Frequency: Monthly \n Probationary Period: 180 days \n Work Arrangement: Hybrid, 3-days per week \n TL;DR Kharon is seeking a full-time Senior Data Scientist, Graph Risk Analytics based in London. RESPONSIBILITIES:\n \n • Taking ownership of Kharon's risk propagation and entity analytics system — the engine that evaluates entities in our knowledge graph and surfaces meaningful risk signals to customers\n, • Designing and implementing complex analytical logic that translate nuanced geopolitical and financial risk into structured, interpretable outputs\n, • Building and maintaining scalable data pipelines and graph-based ML systems that power risk scoring and entity analysis\n, • Partnering closely with Research, Product, and Engineering teams to understand evolving risk frameworks and translate them into robust, maintainable systems\n, • Iterating on the system's architecture to increase the complexity and precision it can handle — this is not a rip-and-replace, but a thoughtful evolution of a system already in production\n, • Exploring how LLMs and other AI techniques can be integrated to handle increasingly complex risk logic\n QUALIFICATIONS:\n \n, • A proven interest or experience in global security, financial crimes, sanctions, export controls, or related domains\n, • 4+ years of experience as a Data Scientist, with demonstrated ownership of production systems\n, • Strong foundation in statistics and the ability to apply quantitative methods to complex, real-world problems\n, • Proficiency in Python, SQL, and working with graph databases or knowledge graph structures\n, • Experience with graph analysis, graph ML, or network analysis — professional experience is a strong differentiator\n, • Comfort working across research and data engineering contexts — this role spans all three\n, • Experience with Docker, Kubernetes, and API development\n, • Strong product instincts — able to go deep technically while staying aligned to customer and business outcomes\n, • Bonus: Experience with LLMs or AI-assisted analytical systems\n ABOUT KHARON:\n Kharon operates at the nexus of global security and is on a mission to revolutionize the current landscape. We take complex data as it relates to global security and empower our clients to not only understand the risk associated with their potential business relationships but to operationalize that data so that they can make the best and most informed decisions possible. \n From financial crimes and sanctions to export controls and threat identifications, our tools optimize protection against the types of risks that could otherwise be incredibly dangerous and excessively costly to any business. Serving many of today’s leading global financial and multinational institutions, Kharon products are the most powerful in the space with a precision and depth that is absolutely unparalleled. \n When you look at any major global crisis event, we’re providing intelligence that’s at the heart of those circumstances. We connect the dots in a way that’s meaningful. As the world continues to evolve in complexity, so too does the demand for our products. Given the significance of our work and the increasing global reliance on our insights, we are looking for a Senior AI Engineer, Agentic Systems to join us as we work to shape the way businesses perceive and navigate global risks. Company Benefits\n \n • Fully-sponsored private health insurance\n, • Pension plan with 3% employer contribution\n, • Annual leave plus bank holidays\n DISCLOSURES\n Kharon is committed to cultivating and maintaining a workplace that is free from harassment and discrimination. All qualified applicants will receive consideration for employment without regard to race, religion, color, national origin, ethnicity, gender, gender identity or expression, sexual orientation or identity, neurodiversity, appearances, age, protected veteran status, or status as a qualified individual with disability. \n We are committed to making reasonable adjustments to support disabled applicants and employees. If you require any adjustment to participate in the recruitment process, please contact apply@kharon.com \n You must have the right to work in the UK. Kharon is unable to offer visa sponsorship for this role. UNITED KINGDOM Candidate Privacy Notice\n Kharon is committed to protecting your personal data in accordance with the UK General Data Protection Regulation (UK GDPR) and the Data Protection Act 2018. We collect the personal data you submit as part of your application — including your name, contact details, employment history, and qualifications — to assess your suitability for the role. Our lawful basis for processing is legitimate interests (Article 6(1)(f) UK GDPR). \n If your application is unsuccessful, your data will be retained for up to 12 months before being securely deleted. If you accept a role, your data will transfer to your employee record. \n You have the right to access, correct, or request deletion of your data, to object to or restrict its processing, and to lodge a complaint with the UK data protection authority, the ICO, at www.ico.org.uk. To exercise your rights, contact us at apply@kharon.com. \n #J-18808-Ljbffr

The Role \n We are looking for an accomplished Principal Geomaterials Scientist to join our highly regarded Geomaterials Department in London. This is an exceptional opportunity for an experienced specialist in petrography and construction materials to take a leading role in complex investigations, work with industry-recognised experts, and contribute to some of the most challenging and high-profile projects in the UK and internationally. \n You will provide technical leadership on a diverse range of investigations involving concrete, mortar, masonry, natural stone and other construction materials. Working alongside geologists, materials scientists, chemists and engineers, you will deliver expert analysis and build trusted relationships with clients. \n You will play a key role in project delivery, technical excellence and the development of junior staff, helping to shape the future growth of the department. The role is primarily laboratory-based in London, with site-based investigations across the UK and occasional international assignments. \n \n Responsibilities \n You will: \n\n • Lead petrographic analysis of construction materials, including concrete, mortar, render and adhesives using optical microscopy and SEM/EDX techniques.\n, • Interpret mineralogical, chemical and microstructural data obtained through SEM and XRD analyses.\n, • Design, manage and oversee laboratory testing and investigation programmes\n, • Lead and support laboratory and site-based investigations.\n, • Manage client relationships and oversee project delivery.\n, • Interpret and analyse technical data and prepare high-quality reports.\n, • Provide technical guidance, mentoring and training to junior colleagues.\n, • Contribute to the continuous development of Sandberg's technical capabilities and reputation within the industry.\n\n \n \n About you \n We are looking for a technically accomplished geomaterials scientist with a passion for investigation, problem-solving and professional excellence. \n Essential Requirements: \n\n • Prior work experience (ideally >10 years in a similar industry) or someone with experience in relevant academia wishing to start working in industry\n, • Degree in Geology, Materials Science, or a related discipline\n, • Chartered Geologist (CGeol)\n, • Advanced petrography skills, including plane-polarised, cross-polarised and reflected light microscopy of concrete and other construction materials\n, • Strong technical report-writing and communication skills\n, • Dynamic work ethic to learn and develop new skills\n, • Demonstrable experience managing projects and interacting directly with clients\n\n \n Desired experience. \n The following experience would be advantageous: \n\n • Concrete petrography, including the identification and assessment of concrete deterioration mechanisms.\n, • Cement chemistry and the behaviour of cementitious materials.\n, • Interpretation and evaluation of SEM/EDX (Scanning Electron Microscopy/Energy Dispersive X-ray) analytical data.\n, • Investigation and assessment of historic and heritage construction materials.\n, • Expert Witness investigations, technical reporting, and the preparation of evidence for legal proceedings\n\n \n \n What we offer \n For more than 165 years, Sandberg has provided independent technical expertise to the construction, engineering and infrastructure sectors. Our reputation is built on scientific rigour, technical excellence and trusted client relationships, which enables us to work on nationally and internationally significant projects. \n Our Geomaterials Department is one of the largest and most technically capable teams of its kind in the UK. It is supported by extensive laboratory facilities including in-house sample preparation capabilities and an advanced microscopy suite containing research grade optical microscope and scanning electron microscopes. We deliver industry-leading investigations into construction materials, geological materials and structural performance. \n We recognise that people are our greatest asset and we foster a supportive and collaborative working environment. We are proud to have a community feel and employ staff from a variety of different backgrounds. We are committed to continuing to develop a diverse and inclusive workplace. We welcome and will consider all applications that meet the above requirements. \n