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At Faculty, we transform organisational performance through safe, impactful and human-centric AI. With more than a decade of experience, we provide over 350 global customers with , and Fellows from our award winning _. Our expert team brings together leaders from across government, academia and global tech giants to solve the biggest challenges in applied AI. Should you join us, you’ll have the chance to work with, and learn from, some of the brilliant minds who are bringing Frontier AI to the frontlines of the world. As a Senior Data Scientist in our Defence business unit you will lead project teams that deliver bespoke algorithms to our clients across the defence and national security sector. You will be responsible for conceiving the data science approach, for designing the associated software architecture, and for ensuring that best practices are followed throughout. You will help our excellent commercial team build strong relationships with clients, shaping the direction of both current and future projects. Particularly in the initial stages of commercial engagements, you will guide the process of defining the scope of projects to come with an emphasis on technical feasibility. We consider this work as fundamental towards ensuring that Faculty can continue to deliver high-quality software within the allocated timeframes. You will play an important role in the development of others at Faculty by acting as the designated mentor of a small number of data scientists, and by supporting the professional growth of data scientists on the project team. The latter includes giving targeted support where needed, and providing step-up opportunities where helpful. Faculty has earned wide recognition as a leader in practical data science. You will actively contribute to the growth of this reputation by delivering courses to high-value clients, by talking at major conferences, by participating in external roundtables, or by contributing to large-scale open-source projects. You will also have the opportunity to teach on the fellowship about topics that range from basic statistics to reinforcement learning, and to mentor the fellows through their 6-week project. Thanks to Faculty platform, you will have access to powerful computational resources, and you will enjoy the comforts of fast configuration, secure collaboration and easy deployment. Because your work in data science will inform the development of our AI products, you will often collaborate with software engineers and designers from our dedicated product team. Senior experience in either a professional data science position or a quantitative academic field Strong programming skills as evidenced by earlier work in data science or software engineering. Although your programming language of choice (e.g. R, MATLAB or C) is not important, we do require the ability to become a fluent Python programmer in a short timeframe An excellent command of the basic libraries for data science (e.g. NumPy, Pandas, Scikit-Learn) and familiarity with a deep-learning framework (e.g. TensorFlow, PyTorch, Caffe) A high level of mathematical competence and proficiency in statistics A solid grasp of essentially all of the standard data science techniques, for example, supervised/unsupervised machine learning, model cross validation, Bayesian inference, time-series analysis, simple NLP, effective SQL database querying, or using/writing simple APIs for models. We regard the ability to develop new algorithms when an innovative solution is needed as a fundamental skill A leadership mindset focussed on growing the technical capabilities of the team; a caring attitude towards the personal and professional development of other data scientists; enthusiasm for nurturing a collaborative and dynamic culture An appreciation for the scientific method as applied to the commercial world; a talent for converting business problems into a mathematical framework; resourcefulness in overcoming difficulties through creativity and commitment; a rigorous mindset in evaluating the performance and impact of models upon deployment Some commercial experience, particularly if this involved client-facing work or project management; eagerness to work alongside our clients; business awareness and an ability to gauge the commercial value of projects; outstanding written and verbal communication skills; persuasiveness when presenting to a large or important audience Experience leading a team of data scientists (to deliver innovative work according to a strict timeline) as well as experience in composing a project plan, in assessing its technical feasibility, and in estimating the time to delivery The Faculty team is diverse and distinctive, and we all come from different personal, professional and organisational backgrounds. We all have one thing in common: we are driven by a deep intellectual curiosity that powers us forward each day. Faculty is the professional challenge of a lifetime. You’ll be surrounded by an impressive group of brilliant minds working to achieve our collective goals. Our consultants, product developers, business development specialists, operations professionals and more all bring something unique to Faculty, and you’ll learn something new from everyone you meet.

Pega CDH Consultants Inside IR35 Remote in UK Initial 6 month engagement emagine is a high-end professional services consultancy and solutions firm specialising in providing business and technology services to the financial services sector. We power progress, solve challenges, and deliver real results through tailored high-end consulting services and solutions. We have created a culture of openness and integrity by building genuine and strong relationships and partnerships, enabling us to be uncompromising in our dedication to delivering the optimal service for our clients. Our commitment is not just towards our clients — we aim to foster a positive and equitable working environment with our consultants and colleagues, which stems from our core values: Confident, Dedicated, Responsible, Genuine. We are building a best-in-class Next Best Action (NBA) decisioning capability and are hiring experienced professionals to design, scale, and optimise decisioning frameworks across multiple markets. This is an opportunity to work at the intersection of data, AI, and customer engagement, delivering personalised, real-time experiences in a regulated environment. We are hiring for: Lead Decisioning Expert Own and govern the NBA decisioning framework across markets. Key Skills: Pega LDA (mandatory) Deep Pega CDH expertise (NBA Designer, decision strategies) Decision frameworks (eligibility, arbitration, prioritisation) Omni-channel decisioning (real-time & outbound) Decision governance, explainability, regulatory awareness Strong stakeholder management & Agile delivery Lead NBA Data Scientist Design and optimise ML models driving NBA decisioning. Key Skills: Pega CDH adaptive models Strong MLB / RTIM / arbitration logic knowledge Advanced Python & ML development A/B testing, uplift measurement, model governance Feature engineering & real-time vs batch decisioning Git, Agile, cross-functional collaboration NBA Decisioning Specialist Deliver decisioning use cases and personalisation strategies. Key Skills: Pega PCDC (mandatory) Pega CDH / NBA Designer experience Decision logic configuration (eligibility, prioritisation, suppression) Testing, simulation & performance optimisation Strong business-facing communication Nice to have: Adobe AEP, Financial Services, multi-market experience Data Integration & System Engineers Build scalable data pipelines supporting decisioning systems. Key Skills: GCP (BigQuery) & Hadoop/Cloudera (mandatory) Spark, Scala, Python, SQL Data pipelines (batch & near real-time) Data modelling, governance & CI/CD Pega CDH integration experience QA / Test Specialists Ensure quality and performance across data and decision platforms. Key Skills: Hadoop & GCP (mandatory) Test automation (Pytest, Robot Framework) Python, SQL, Bash CI/CD, Docker, Jenkins ISTQB certified Our People The ideal consultants will share our values and be aligned with our ways of working. As your career progresses, you can expect to work across all areas of the project lifecycle, from strategy to implementation. This will provide you with a broad base of experience from which to build an outstanding career. The ideal consultants will share our values and be aligned with our ways of working and as your career progresses, you can expect to work across all areas of the project lifecycle. We pride ourselves on; Providing our people with a supportive culture, rooted in our values and driven by our purpose. Promoting a culture of inclusion, collaboration, well-being, and learning and development. Providing increased agility and flexibility within our hybrid working model Investing in employees’ growth through ongoing training and development Autonomy to take ownership of projects, making decisions and demonstrating individual expertise Providing an transparent performance and career management experience. Our consultants are integral to delivering successful consulting engagements, addressing our clients’ most pressing business challenges, and build lasting value in disciplines such as: Solve sophisticated, ambiguous business, change and technology problems, bringing structure and meticulous analysis and planning, acting, and taking decisions with little strategic direction Build, develop and sustain trusted senior client relationships in the C-suite by remaining highly attuned to client needs Drive, enable and support the business, partnering with our leaders, clients, and consultants across our practices to take the best of emagine to our clients through opportunity identification/qualification, solution development/presentation Interested? At emagine, we are committed to building an international and diverse team by embracing our different backgrounds. If you are up to the challenge and would like to find out more, get in touch with us immediately, our internal recruitment team is always keen to hear from dynamic individuals that are looking to further their career and explore their full potential. “emagine is an equal opportunity employer, and employment practices are based strictly on merit. It is the policy of the Company to give equal opportunity in employment regardless of sex, sexual orientation, marital status, race, age, disability, gender reassignment, pregnancy and maternity, religion or ethnic origin

About TetraScience TetraScience is the Scientific Data and AI Company building Tetra OS, the operating system for scientific intelligence. We help the world’s leading life sciences firms turn fragmented scientific data into AI-native assets and scientific workflows that accelerate discovery, development, and manufacturing. TetraScience’s growing ecosystem of strategic partners includes NVIDIA, Databricks, Thermo Fisher Scientific, Snowflake, Google, and Microsoft. In connection with your candidacy, you will be asked to carefully review “_,” authored by our CEO, Patrick Grady; it is impossible to overstate the importance of this document, and you should take it literally as you decide whether our mission, culture, and expectations are right for you. What You Will Do TetraScience is looking for a Technical Enablement Lead / Developer Relations Lead for the EU. The ideal candidate should have expertise in customer and field enablement, adult learning principles, educational program creation, use case architecture and implementation, and a genuine passion for Data and AI technologies. The candidate should be driven by a desire to educate and inspire, and have the technical skills to quickly prototype new ideas and solutions. And finally, the candidate should seek to ensure developers can be successful with minimal friction, and champion product and process changes that make this a reality. You will work to understand the needs of different user personas (data scientists, machine learning engineers, scientists and R&D IT analysts), analyze their data environment, assist in the design and implementation of self-service solutions, and create training artifacts to accelerate adoption and growth. This is a technical enablement role, interfacing between internal and external stakeholders including; sales teams, technical teams, customers and potential customers. Your expertise not only covers the technical aspects of data integration, storage, access and architectures but also includes the skills to convey complex technical concepts in a way that aligns with business needs and potential solutions. Your work will directly impact how developers adopt TetraScience’s Scientific Data & AI Cloud, leverage new platform capabilities, and innovate in our ecosystem. You’ll collaborate closely with Product, Platform Engineering, Field Engineering, Customer Engagement & Support, Sales, and Marketing teams to empower customers, technical field team members, and all customer-facing technical roles through exceptional enablement programs. You’ll set the strategy for EU developer experience and community, including partners, customers, and independent developers; and be responsible for how developers discover, onboard, build, and scale applications. This role will be pivotal in growing our developer ecosystem, gathering crucial feedback to inform product development. Your work will educate and inspire the biopharmaceutical industry as to the power of an open ecosystem where precisely engineered scientific data flows freely and without restrictions. Your success in this role will directly shape TetraScience's growth trajectory and market position while ensuring our platform is accelerating science and patient outcomes across countless use cases. Responsibilities • Scientific & Domain Expertise, • Deep understanding of pharmaceutical/life sciences R&D workflows, data, and scientific principles, • Ability to engage credibly with data scientists, lab scientists, and R&D IT stakeholders, • Technical Skills, • Able to code and build practical solutions using scientific data platforms, pipelines, and apps, • Translate complex technical problems into working implementations within a pharma context, • Training & Enablement, • Design and deliver in-person training sessions, workshops, and demonstrations for both technical and non-technical audiences, • Create supporting materials: tutorials, documentation, sample code, and best practice guides, • Communication & Collaboration, • Translate technical and scientific concepts into clear, accessible language for non-technical stakeholders, • Collaborate with Product, Engineering, and UX teams to surface customer feedback as actionable requirements Must Have: • 2+ years professional experience in a Life Sciences company and/or a scientific background, • 3+ years professional experience as data scientist, scientific data engineer, or solutions architect, • 2+ years professional experience in technical enablement and/or developer relations, • Solid experience running large scale enablement programs, and how to evangelize and roll out the programs effectively across the organization, • Exceptional communication, storytelling, and presentation skills, coupled with a strong executive presence and the ability to effectively influence and engage large audiences, • Strong technical background with hands-on experience in SQL, Python, and modern data stack technologies, • Deep understanding of drug discovery, development, and manufacturing processes, • Ability to travel regularly to customer locations and whiteboard the product strategy with them, • Experience with data governance, privacy, and compliance considerations, • Exceptional stakeholder management skills with ability to influence C-level executives, • Ability to deal with ambiguity and thrive in a constantly changing and evolving work environment, • Experience working with high-bandwidth and high-energy professionals, • Insatiable curiosity to learn, develop, and grow year-over-year, • Great interpersonal skills and an ability to coordinate and drive initiatives supporting multiple teams Nice To Have: • Experience at high-growth SaaS companies with complex data needs, • Previous experience as a practicing bench scientist is highly valued, • Previous experience within a biopharma company in an IT related function is a big plus, • Background in technical support / field service highly valuable - this demonstrates your ability to internalize complexities and tailor explanations for a given audience, • Familiarity with enterprise sales processs within the pharmaceutical sector, • Experience with AWS application stack, • Competitive Salary and equity in a fast-growing company., • Supportive, team-oriented culture of continuous improvement., • Generous paid time off (PTO)., • Flexible working arrangements - Remote work. We are not currently providing visa sponsorship for this position

At Wayve we're committed to creating a diverse, fair and respectful culture that is inclusive of everyone based on their unique skills and perspectives, and regardless of sex, race, religion or belief, ethnic or national origin, disability, age, citizenship, marital, domestic or civil partnership status, sexual orientation, gender identity, veteran status, pregnancy or related condition (including breastfeeding) or any other basis as protected by applicable law. Founded in 2017, Wayve is the leading developer of Embodied AI technology. Our advanced AI software and foundation models enable vehicles to perceive, understand, and navigate any complex environment, enhancing the usability and safety of automated driving systems. Our vision is to create autonomy that propels the world forward. Our intelligent, mapless, and hardware-agnostic AI products are designed for automakers, accelerating the transition from assisted to automated driving. In our fast-paced environment big problems ignite us—we embrace uncertainty, leaning into complex challenges to unlock groundbreaking solutions. We aim high and stay humble in our pursuit of excellence, constantly learning and evolving as we pave the way for a smarter, safer future. At Wayve, your contributions matter. We value diversity, embrace new perspectives, and foster an inclusive work environment; we back each other to deliver impact. Make Wayve the experience that defines your career! We’re looking for a senior Applied Scientist to lead the design and experimentation of Wayve’s core pretraining datasets for foundation models in embodied AI. This is a high-impact opportunity to shape the data that drives model generalization across cities, embodiments, and reasoning tasks. You'll work across research, data, and engineering teams to build world-class multi-modal datasets and define how we evaluate and improve them at scale. • Lead the design, curation, and analysis of large-scale pretraining datasets for embodied AI, • Develop and run data-centric experiments to optimize training effectiveness and generalization, • Collaborate with cross-functional teams in London, Sunnyvale, and Vancouver on data architecture and strategy, • Define and implement metrics and benchmarks to assess dataset quality and model-data interactions, • Contribute to research outputs, tools, and processes that elevate data as a core lever for progress What you’ll bring to Wayve In order to set you up for success as a Senior Applied Scientist at Wayve, we’re looking for the following skills and experience. Essential • 3–5 years of experience post-PhD, or equivalent experience in industry with a focus on dataset design, multi-modal learning, or pretraining, • Strong applied research track record, including publications in venues such as NeurIPS, ICML, ICLR, CoRL, CVPR, or similar, • Hands-on experience curating, filtering, and scaling large datasets (vision, video, or multi-modal) for machine learning models, • Proficiency with machine learning frameworks (e.g., PyTorch) and large-scale data processing (e.g., Ray, Spark, Flyte and other distributed compute infrastructure), • Ability to design and run scientific experiments to evaluate dataset impact on model performance, • Strong communication and collaboration skills, with experience working across technical and cross-functional teams Desirable • Experience with foundation model training pipelines and data selection for large-scale pretraining, • Familiarity with multi-modal, temporal, or sensor-rich datasets (e.g., video, LiDAR, text), • Contributions to benchmark design, data-centric evaluations, or open-source tooling for dataset experimentation, • Attractive compensation with salary and equity, • Immersion in a team of world-class researchers, engineers and entrepreneurs, • A unique position to shape the future of autonomy and tackle the biggest challenge of our time, • Bespoke learning and development opportunities, • Relocation support with visa sponsorship, • Flexible working hours - we trust you to do your job well, at times that suit you and your time, • Benefits such as an onsite chef, workplace nursery scheme, private health insurance, therapy, daily yoga, onsite bar, large social budgets, unlimited L&D requests, enhanced parental leave, and more! This is a full-time role based in our office in London. At Wayve we want the best of all worlds so we operate a hybrid working policy that combines time together in our offices and workshops to fuel innovation, culture, relationships and learning, and time spent working from home. We understand that everyone has a unique set of skills and experiences and that not everyone will meet all of the requirements listed above. If you’re passionate about self-driving cars and think you have what it takes to make a positive impact on the world, we encourage you to apply. For more information visit _ To learn more about what drives us, visit _ DISCLAIMER: We will not ask about marriage or pregnancy, care responsibilities or disabilities in any of our job adverts or interviews. However, we do look to capture information about care responsibilities, and disabilities among other diversity information as part of an optional DEI Monitoring form to help us identify areas of improvement in our hiring process and ensure that the process is inclusive and non-discriminatory.

Technical Account Manager London - Hybrid or UK - Remote About Snowplow Snowplow is the global leader in customer data infrastructure for AI, enabling every organisation to transform raw behavioural data into governed, high-fidelity fuel for AI-powered applications—including advanced analytics, real-time personalisation engines, and AI agents. Digital-first companies like Strava, HelloFresh, Auto Trader, Burberry, and DPG Media use Snowplow to collect and process event-level data in real time, delivering it securely to their warehouse, lake, or stream, and integrate deep customer context into their applications. Thousands of companies rely on Snowplow to uncover customer insights, predict customer behaviours, hyper-personalise customer experiences, and detect fraud in real time. The Opportunity The Technical Account Manager (TAM) sits within our Technical Services team and reports to the Technical Account Management Lead. This customer-facing role blends technical expertise with consultative support, helping customers solve problems and get value from their data using Snowplow. We view customer activation as key to retention and success. TAMs work closely with clients to understand their data goals and design tailored implementations that drive business outcomes. We’re looking for a technically savvy, data-driven individual who thrives in a fast-paced environment and enjoys working with data teams to co-design solutions, implement use cases, and demonstrate impact. The role involves close collaboration with cross-functional teams—Engineering, Product, Sales, Support, and Marketing—to optimise customer strategies and expand use cases. What you'll be doing: ● Partner with various Snowplow team members to support customer accounts, collaborating with them to deliver value within their unique and complex organisations.● Provide consultation and advisory support to customers regarding solutions and use case development, by providing actionable execution of success criteria and solutioning complex problems.● Work with customers to identify, diagnose and resolve technical challenges with their Snowplow solution – including front-end implementation, data modelling, real-time data processing, and more.● Educate and enable our customers through tailored workshops and advisory sessions.● Collaborate with our Solution Architects, to develop and evolve technical assets such as data models, implementation strategies, architectures, and supporting code to bring value to our customers as well as our internal teams.● Develop domain expertise in key verticals through deep customer collaborations, general research and industry events/conferences.● Work closely with the Customer Success and Strategic Account Management teams to develop long-term strategies and roadmaps for activation and adoption of Snowplow’s products. ● Continue learning and staying current with our products and related technologies, to assist and train both customers and other team members We’d Love to Hear From You If Have: ● A solid understanding of the data space - cloud infrastructure, database technologies, visualisation tools and other enabling technologies in the modern data stack.● Experience working either client-side or agency-side as an analyst, analytics engineer, data engineer, data consultant, or data scientist.● SQL and data modelling experience, and proficiency at manipulating data.● Experience with direct management of a customer portfolio for continual successPrevious experience designing and implementing complex software solutions, including gathering/developing requirements and interacting with senior technical stakeholders (e.g. CTO, VP, Tech Lead). ● Previous experience of using Snowplow, (either BDP or open source) is ideal but not required What We Offer You in Return: 💰 A competitive package, including share options🧘 Flexible working🏖 A generous holiday allowance no matter where you are in the world💻 MacBook and home office equipment allowance👪 Enhanced maternity, paternity, shared parental and adoption leave Snowplow is dedicated to building and supporting a brilliant, diverse and hugely inclusive team. We don't discriminate against gender, race, religion or belief, disability, age, marital status or sexual orientation. Whatever your background may be, we welcome anyone with talent, drive and emotional intelligence.

Data Scientist 1 day a month in London (expensed) We are working with a networking organisation that specialises in financial services. They are looking to add their first Data Scientist to the team to lead on projects from start to finish. You will build a scoring model to match customers to the client and be able to work closely with stakeholders. You will need: • 3-5 years Data Science experience, • Python & SQL, • Predictive Modelling, Statistical Analysis experience, • Strong communication and stakeholder skills, • Have worked in a small organisation

Description Brego is an automotive technology company using AI and data analytics to help dealerships, lenders, and other industry partners make better vehicle valuation, pricing, and risk decisions. Working at the intersection of software, data, and decision-making, the team focuses on turning complex information into practical products that support smarter outcomes across the automotive market. As a Lead Data Scientist, you will take ownership of the AI (custom neural networks rather than third-party LLM technology) and machine learning capabilities behind products that influence high-value pricing and risk decisions. This is a hands-on technical leadership role where you will be responsible for designing, building, deploying, and continuously improving production machine learning systems from end to end. You will own the full lifecycle of models, from feature engineering and training through deployment, monitoring, retraining, and ongoing optimisation, working independently while collaborating closely with engineering and product teams to deliver measurable business impact. • Own the end-to-end lifecycle of production machine learning models, from problem definition through deployment and ongoing optimisation., • Design, build and deploy artificial neural network and machine learning models for vehicle valuation, pricing and other analytics., • Take responsibility for production model performance, reliability and long-term maintenance., • Evaluate model performance and improve predictive accuracy across production models., • Develop and maintain automated retraining pipelines to keep models effective over time., • Monitor deployed models, investigate issues and implement improvements to ensure models remain accurate and reliable., • Design and run experiments, track results and use data to drive model improvements., • Work closely with engineering and product teams to integrate models into production systems and deliver business value. Requirements Must have: • 5+ years of experience building and deploying machine learning models in production environments., • Strong experience developing and training neural networks for real-world applications., • Strong experience with the Python data science ecosystem, including pandas, NumPy and scikit-learn., • Hands-on experience with PyTorch or TensorFlow., • Strong understanding of machine learning, statistics, and model evaluation methodologies., • Experience taking machine learning models from concept through deployment and ongoing production ownership., • Experience evaluating model performance, improving predictive accuracy, and maintaining retraining pipelines, model monitoring, and experiment tracking., • Experience with feature engineering and working with large, real-world datasets., • Experience writing clean, maintainable, production-quality Python code., • Experience with SQL for data analysis and data manipulation., • Experience deploying ML workloads in cloud environments., • Ability to independently own technical projects and make sound engineering decisions with minimal supervision., • Strong problem-solving skills with the ability to investigate complex data and modelling challenges., • Strong communication skills, with the ability to explain technical concepts to both technical and non-technical stakeholders., • Experience collaborating with software engineers, product managers, and data engineers., • Eligible to work in the UK. Nice to have: • Experience in the automotive industry or with vehicle data., • Experience in pricing, forecasting, risk modelling, or other predictive analytics domains., • Experience with MLOps tooling and infrastructure., • Experience building automated data and model pipelines., • Experience mentoring or providing technical leadership to other data scientists or engineers. Benefits • Competitive salary of £90,000 - £110,000 per year, depending on experience., • Private healthcare., • Pension scheme., • Fully remote role with flexible working hours., • Working from home allowance., • Choice of Apple MacBook Pro or high-spec Windows workstation., • Learning and progression opportunities., • Optional access to our Silverstone office. The team usually meets there around one day per week, but attendance is entirely optional., • High levels of ownership and autonomy with the opportunity to shape the company’s AI strategy., • Collaborative, low-bureaucracy engineering culture that values autonomy, integrity and innovation., • Regular company social events., • 25 days annual leave plus 3 additional days between Christmas and New Year.

As a Lead Data Scientist, you'll take on a pivotal, entrepreneurial role, functioning as the technical expert who thrives on complexity and commercial impact. Mentoring and developing other data scientists and team members, actively contributing to the growth and technical excellence of the organisa

We are a first-mile intelligence platform, delivering granular visibility into the point of origin in global ag & soft commodity supply chains - where risk, cost, performance and exposure are set. You’ll join a global, cross-functional team that values rigour, curiosity and working close to real-world challenges. Whether your focus is AI, climate, product or operations, you’ll have space to contribute meaningfully and make an impact from day one. If you’re excited by complex problems and want to help reshape how nature is valued in real-world decision-making, we’d love to hear from you. We are hiring a Machine Learning Scientist into the Science Team to contribute to the development of models — from classical statistics and gradient-boosted methods through to deep learning when warranted — that turn satellite, radar, and LiDAR observations into defensible, plot-level intelligence on the world's commodity supply chains. You will work across the full lifecycle — from research and prototyping through to validated, productionised models. A meaningful fraction of the team's work centres on building lightweight downstream models — classifiers, regressors, similarity-search workflows. Likely focus areas for this role include: Commodity and plantation mapping by region - palm oil, cocoa, coffee, rubber, soy, timber and similar - in support of EUDR compliance and supply-chain due diligence. Forest degradation and biomass / canopy-height estimation from multi-sensor fusion. Develop ARR feasibility models that fuse climate, soil, and remote-sensing inputs to estimate site potential, forecast biomass and carbon trajectories, and quantify physical and permanence risk. Design, train and evaluate ML models - from gradient-boosted methods to CNNs, U-Nets and vision transformers - for commodity and plantation mapping, land-cover classification, change and disturbance detection, and biomass / canopy-height estimation. Build embedding-driven workflows on top of EO foundation models - few-shot classifiers, similarity search, downstream regressors. Design validation strategies that benchmark outputs against plot inventories and third-party reference datasets, quantify uncertainty, and surface failure modes; produce QA artefacts (maps, plots, model cards, error analyses) that internal teams and clients can trust and defend. Partner with Engineering to take models into scalable, reproducible inference pipelines across millions of plots, and contribute to a strong research culture across Science, AI and Engineering - reviewed code, shared tooling, and active engagement with EO/ML literature. Degree in a quantitative field: environmental/earth science, computer science, physics, maths, engineering, or similar. 3+ years of applied machine-learning experience, including time spent in an industry, product, or startup setting i.e. shipping models. Expertise in geospatial Python tooling: rasterio, xarray, geopandas, GDAL, and the STAC ecosystem. Hands-on experience training, evaluating, and debugging ML models across the modern Python stack - deep learning (CNNs, U-Nets, vision transformers) using PyTorch, as well as classical methods (gradient boosting, random forests) with scikit-learn. Demonstrable experience with remote sensing data (optical, SAR) and an understanding of the sensor-specific quirks that matter for modelling. Comfortable with Git, cloud compute (AWS or similar), and collaborative codebases. Clear written and verbal communication: can explain modelling choices, uncertainties, and trade-offs to scientific and non-scientific stakeholders. Domain exposure: deforestation, land-use change, biomass / canopy-height estimation, climate risk, or supply-chain transparency. Experience using EO foundation models as a downstream substrate - building lightweight classifiers, regressors, or similarity-search workflows on top of frozen embeddings (e.g., AlphaEarth Foundations, Clay, etc). Comfortable fine-tuning or pretraining where the case justifies it. Multi-modal fusion experience - combining optical (Sentinel-2, Landsat), SAR (Sentinel-1, PALSAR), and/or LiDAR (GEDI, ICESat-2) into unified predictions. Time-series modelling for environmental change detection - temporal transformers, sequence models, or self-supervised approaches. Comfortable building with AI-assisted development tools as a core part of your workflow. Familiarity with Google Earth Engine, Microsoft Planetary Computer, AWS Open Data, or other STAC-based catalogues. Experience working in cross functional teams working alongside solutions architects, sales, and engineering. You’ll report to the Science Team Lead and partner day-to-day with the wider Science Team while working closely with Engineering and Product teams. This is a Science Team role with regular touch points with Engineering and Product - the interview process gives you a chance to meet your immediate team and a couple of key partners. Recruiter screen (30 min) Hiring manager (45-60 min) Science Team technical interview (45 min) Engineering and/or Product interview (30 min) Potential in-person problem-solving session with the team - designed to be interactive and a glimpse of what being part of the Science Team will be like! Accessibility: Tell us if you need adjustments, we’ll accommodate. What you’ll gain at Treefera Build something that matters - join a high-growth climate-tech company applying AI, satellite data and quantitative modelling to real-world challenges across global supply chains, commodities and carbon. Work on complex, meaningful problems - develop systems that balance risk, resilience, compliance and sustainability, giving organisations a genuine information advantage at global scale. Collaborate with exceptional people - work alongside scientists, engineers and operators who are leaders in their fields, combining academic rigour with practical, cross-functional product delivery. Ship and grow in a high-trust environment - experiment, iterate and take thoughtful risks in a team that values autonomy, creativity and continuous learning. Develop your craft - dedicated space and time to grow your skills toward mastery, tackling technically demanding challenges that push the boundaries of applied AI and environmental data. Be rewarded for your impact - competitive compensation, equity options, meaningful benefits, and the opportunity to help shape the future of AI-powered risk and environmental intelligence. Diversity, Equity & Inclusion Bold solutions come from diverse teams. Please refer to our DEI & EEO commitment below. If you need any accommodation during the application process, we’re here to support you. Learn more about how we think and build Many of our engineers, scientists and product leaders share their thinking publicly. Explore the Treefera _ for technical deep dives, research and product perspectives. Privacy notice By applying to Treefera, you consent to the processing of your personal data in line with our _.

About AQEMIA AQEMIA is a next-gen pharmatech company generating one of the world's fastest-growing drug discovery pipeline. Our mission is to design fast innovative drug candidates for dozens of critical diseases, such as immuno-oncology. Our unique approach leverages quantum-inspired physics algorithms to power generative AI in designing novel drug candidates—without relying on experimental data. We already delivered several drug discovery successes within our internal pipeline and through collaborations with pharmaceutical companies. Our most advanced programs are currently in vivo optimization. About the team you’ll join:As a Senior AI Research Scientist, you will join one of Aqemia’s Drug Discovery Platform AI Teams, composed of 5 AI Researchers, and lead efforts to develop cutting-edge AI algorithms to model protein-ligand systems and predict molecular properties. You will be a hands-on technical expert pushing the boundaries of what AI can do for drug discovery. Your deep knowledge of machine learning, strong coding foundations, and applied experience in model development will play a key role in advancing our Drug Discovery Platform.You will act as a technical mentor, contribute to high-impact R&D projects, and help integrate innovative AI methodologies into real-world drug discovery applications. • Lead the design and the technical implementation of novel ML algorithms with a strong focus on deep learning, generative models, graph neural networks, and physics-informed AI to predict molecular properties and protein-ligand interactions., • Take part in cutting-edge research and bibliographic exploration. You’ll identify relevant recent publications, benchmark promising ideas, and propose model or pipeline improvements., • Act as a mentor to junior team members, offering guidance on system design, model implementation, debugging, and good coding practices., • Collaborate with AI researchers, computational chemists, and drug discovery teams to translate AI models into actionable scientific insights., • Be deeply involved in coding, from prototyping to deploying production-ready models. You should have a strong software engineering mindset and a passion for writing clean, efficient, and scalable code., • Share best practices in deep learning model development, testing, and reproducibility within the team., • Scale AI models for real-world applications, optimizing model efficiency, interpretability, and generalization to unseen chemical spaces., • Strong problem-solving skills, autonomy and a collaborative mindset., • PhD or equivalent practical experience in Machine Learning, Computer Science, Applied Mathematics or a related field, with at least 8 years of experience., • Strong programming skills in Python and proficiency with Deep Learning frameworks (e.g., PyTorch, JAX, TensorFlow)., • Demonstrated hands-on experience implementing and deploying deep learning models in production or research environments., • Strong scientific rigor, curiosity, and ability to perform bibliographic research and exploratory R&D., • Experience in drug discovery, chemistry, or physics., • Experience with physics-informed ML models., • Familiarity with high-performance computing (HPC) and cloud-based ML pipelines.Interview Process- Screening call with Talent Acquisition (30 min)- Interview with your future Manager (45 min)- 1st technical interview: Paper review (1.5 hours)- 2nd technical interview: Take-home ML case (1.5 hours)- Interview with VP Platform and co-founders (1 hour each) Preferred MindsetAt Aqemia, we believe that great science thrives in the right mindset and culture. We are looking for candidates who embody the following principles: Pragmatic and Impact-Driven – Focused on delivering solutions that work in real-world applications, balancing scientific rigor with practical usability.Eagerness to Learn – A strong curiosity for scientific advancements and a willingness to continuously expand your expertise.Love for High Scientific Challenges – Enthusiasm for tackling complex problems at the frontier of AI and drug discovery.Team-Oriented – A collaborative spirit, thriving in an interdisciplinary environment.Humility – Open to feedback and different perspectives, always striving for improvement. Aqemia’s Recruitment team leads all recruitment activities for the company. We will not recognise any notional ownership recruitment companies claim over candidates presented directly to hiring managers without our Recruitment team's consent. Unsolicited resumes sent to us from recruiters do not constitute any type of relationship between the recruiter and Aqemia, and we will not be obligated to pay fees should we hire from those resumes. Why Join Us ? At AQEMIA, we work for a mission: joining us means having your own impact on changing the way drugs are discovered, and helping to shape the direction of our fast-growing company and team. Expanding Drug Discovery Pipeline : Focused on critical therapeutic areas like Oncology, CNS, Immuno-inflammation... with in vivo proof of concept/patent stage programs. Collaborations with top Pharma, including a $140M Sanofi deal.Interdisciplinary Team : brilliant talent from tech and life sciences.DeepTech Recognition: Part of French Tech 120 and France 2030.Prime Location : Based in central Paris and London (King's Cross) with the possibility of 2 remote days per week.International Environment : The work language is English - relocation support and French lessons granted if needed.Strong Financial Backing : $100M raised from leading European and International investors

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