76 to 100 of 102 Feature Engineering Jobs in the UK

risk of mental health problems prior to first contact with services. The role is highly collaborative and will involve close working with clinical, engineering, and operational colleagues across CADRE's partner institutions, as well as with academic and NHS co-investigators. Although employed by Cambridgeshire and Peterborough NHS Foundation … attached job description and person specification for full details of responsibilities. Working with data prepared and quality-assured by the CADRE data engineering team, the postholder will contribute to longitudinal analyses of the cohort, including: Describing the cohort at index event (first contact with health, education, or social care ...

dynamics, stochastic rates, jumps, correlation, curve construction, proxying, aggregation, and risk decomposition.Assess statistical, data science, and machine learning approaches where relevant, including calibration quality, feature engineering, validation metrics, explainability, and monitoring.Review implementation and data lineage, including upstream dependencies, market data, sensitivity generation, system flows, and downstream usage.Leverage approved … maintaining awareness of industry developments, regulatory expectations, and market practices.Required Qualifications, Capabilities, and Skills:Strong quantitative background in mathematical finance, statistics, applied mathematics, physics, engineering, computer science, or a related discipline.Practical coding ability in Python or a comparable programming language, with experience using data analysis to investigate technical questions.Understanding ...

economic return optimization. You'll develop calibration frameworks, ensure compliance with regulatory and fairness standards, and explore novel methodologies — including LLMs for explainability and feature engineering. Collaborating with cross-functional teams, you'll translate modeling insights into strategic credit policies and business value, while mentoring junior team members ...

detection, forecasting, behavioural signals, and prediction, ensuring they are accurate, explainable, resilient, and regulator-ready.Own the full model lifecycle from problem framing, data exploration, feature engineering, back-testing, validation, deployment, monitoring, tuning, and incident response when models degrade or fail in production.Partner closely with engineering, data platform … lifecycle.Strong hands-on technical skills, with the ability to work directly with data, code, ML frameworks, and complex datasets, while partnering effectively with software engineering and platform teams.Experience building scalable, reliable, and explainable AI/ML solutions that meet operational, governance, and regulatory requirements and deliver measurable business outcomes.Additional ...

using the latest advances in deep learning and machine learning to personalize recommendations at BumbleOwn defined problems end-to-end, from data exploration and feature engineering through to model training, evaluation, and production deploymentApply modern ML frameworks (e.g., PyTorch or TensorFlow) to design, train, and optimise models … researching or applying machine learning, especially if in recommender systems, ranking or personalisationGood understanding of MLOps and infrastructure concepts: CI/CD for ML, feature stores, model serving, observability, and versioning.Familiarity with containerisation and cloud-native environments (e.g. Docker, Kubernetes, GCP).Familiarity with experimentation methodologies such as A/ ...

testing, quasi-experimental methods, and stakeholder-facing insight delivery. Key Responsibilities Analytical discovery and opportunity identification. Value case assessment. Data preparation and ETL support. Feature engineering collaboration with Data Scientists. Testing and evaluation of interventions. Experiment execution and results analysis. Presenting outcomes to senior stakeholders. Influencing business decisions ...

rankers.Entity/relationship extraction/resolutionKnowledge Graphs; building and inference, graphRAGRecommendation systems and ranking: personalisation, learning-to-rank, feed ranking, user modelling, etc.Tabular ML: feature engineering, structured data modelling (GBDTs, etc.)Statistical & Predictive Modelling: supervised ML, anomaly detection, temporal modelling, etc.Deep understanding of the GenAI landscape and agentic ...

rigorous validation automation (such as backtesting and slice-based evaluation) to prevent data leakage, over-fitting, and production regressions.Engineering Partnership & Handovers: Collaborate closely with Engineering Leads to ensure compute/GPU infrastructure supports model requirements. Clearly define model failure modes, edge cases, and confidence thresholds—to enable SWE partners … build robust fallback systems.Applied Debugging & Guardrails: Diagnose complex algorithmic bugs and implement automated checks for "Silent Failures" (e.g., concept drift or production feature distribution shifts). Lead team-level post-mortems and resolve blocking corrective actions.Career Multiplier: Formally mentor mid-level and associate ML scientists, reviewing their experimental logic ...

software and technical infrastructure. The role involves the development and maintenance of sophisticated tools for alpha research along with the production systems used in feature engineering, portfolio construction, and trade execution.The ideal candidate should be an expert engineer with a deep theoretical foundation, extensive systems design experience … Numpy, Polars, Scikitlearn, Pytorch, etc.DevOps: version control, testing frameworks, release processes, build systems.Excellent communication, problem-solving, and analytical skills.Preferred ExperienceExtremely strong computer science or engineering background with 5+ years of experience.Experience designing and implementing:Distributed Systems.Real-time event-driven systems.Large-scale time series data ingress, storage and processing.Experience with ...

come beyond. Our UK customers can also save, invest and combine their pensions with us. With our hot coral cards and get-paid-early feature, combined with financial education on social media and our award winning customer service, we have a long history of creating magical moments … scales into new marketsshaping how advanced ML and AI can create real value in BorrowingYou’ll partner closely with leaders across Credit Strategy, Product, Engineering, Model Validation, Data, and Platform, and influence decisions that shape both business performance and the long-term architecture of credit decisioning at Monzo. What ...

come beyond. Our UK customers can also save, invest and combine their pensions with us. With our hot coral cards and get-paid-early feature, combined with financial education on social media and our award winning customer service, we have a long history of creating magical moments … scales into new marketsshaping how advanced ML and AI can create real value in BorrowingYou’ll partner closely with leaders across Credit Strategy, Product, Engineering, Model Validation, Data, and Platform, and influence decisions that shape both business performance and the long-term architecture of credit decisioning at Monzo. What ...

driven choices made through the analysis of actuarial experience, profitability drivers, trends and capital requirements. Working alongside Actuarial, Data Science, Business Intelligence and Data Engineering teams, the position focuses on developing and enhancing analytical models, data processes and insights that help deliver scalable solutions and drive commercial value across … business.Key ActionsSupport the ownership, maintenance and continuous development of actuarial data assets, including feature engineering processes and experience analysis models used across the Life businessAnalyse lapse, claims, retention and business mix experience to identify trends, monitor performance and provide insights that support strategic decision makingDesign, build, test ...

driven choices made through the analysis of actuarial experience, profitability drivers, trends and capital requirements. Working alongside Actuarial, Data Science, Business Intelligence and Data Engineering teams, the position focuses on developing and enhancing analytical models, data processes and insights that help deliver scalable solutions and drive commercial value across … business. Key Actions Support the ownership, maintenance and continuous development of actuarial data assets, including feature engineering processes and experience analysis models used across the Life business Analyse lapse, claims, retention and business mix experience to identify trends, monitor performance and provide insights that support strategic decision making ...

doing Develop and deploy ML and statistical models across credit risk, affordability and pricing Own models end-to-end, including data, feature engineering, modelling, validation, deployment and monitoring Build model monitoring frameworks and performance dashboards Explore new data sources, challenger models and A/B testing to improve ...

typically lead a team or the solution delivery effort, demonstrating technical excellence through leading by example. You could be providing technical support, leading an engineering team or working across multiple teams as a subject matter expert who is critical to the success of a large programme of work.Your team … code quality and deployments.Shape team behaviour for writing specifications and acceptance criteria, estimating stories, sprint planning and documentation.Actively define and evolve PA’s data engineering standards and practices, ensuring we maintain a shared, modern and robust approach.Lead and influence technical discussions with client stakeholders to achieve the collective ...

Azure would be great though. Looking for the below skill set: ✅Strong experience delivering applied data science or ML projects end‐to‐end, including feature engineering, model selection, evaluation, and iteration. ✅Strong experience developing solutions in Python, with good practices around code structure, testing, and version control. ✅Experience ...

your results will be measured objectively via A/B testing, directly impacting our business results. We collaborate closely with the analytics, product, and engineering teams. In this role, you will: Develop, implement, and optimize machine learning models that power data‐driven features and products, from problem framing through … analysts to translate ambiguous business problems into well‐scoped ML solutions, including data requirements, modeling approach, and success metrics. Apply strong data modeling, feature engineering, and model selection skills across multiple domains, ensuring models are robust, explainable, and performant at scale. Safely integrate and operate AI/ ...

technical leadership across the full lifecycle of machine learning systems powering a new matching platform. This role is accountable for defining ML architecture, establishing engineering standards, driving MLOps maturity, and ensuring that our models are scalable, secure, explainable, and governed to enterprise‐grade standards.You will contribute to the strategic … governance and compliance framework.This is a highly hands‐on, highly technical, principal‐level role that combines architectural vision with deep practical expertise in ML engineering and AWS-native MLOps.Key ResponsibilitiesTechnical Leadership & ArchitectureDefine the end‐to‐end ML architecture for the matching platform, including data pipelines, model training workflows, inference ...

technical leadership across the full lifecycle of machine learning systems powering a new matching platform. This role is accountable for defining ML architecture, establishing engineering standards, driving MLOps maturity, and ensuring that our models are scalable, secure, explainable, and governed to enterprise‐grade standards.You will contribute to the strategic … governance and compliance framework.This is a highly hands‐on, highly technical, principal‐level role that combines architectural vision with deep practical expertise in ML engineering and AWS-native MLOps.Key ResponsibilitiesTechnical Leadership & ArchitectureDefine the end‐to‐end ML architecture for the matching platform, including data pipelines, model training workflows, inference ...

working closely with Reserving and Claims Analytics teams. Own documentation and governance for model approval ahead of deployment. Test new data sources, factors and feature engineering to continually improve model predictiveness. Present model performance against agreed KPIs to key stakeholders. Mentor junior analysts, embedding best practice across ...

periods of days to weeks. Role: Quantitative Researcher for Alpha Gen (Cross-Asset). Responsible for full lifecycle research from data curation/validation, feature engineering, model development and signal generation. Role is sitting in a central research team responsible for bridging the gap between systematic and discretionary ...

domain.Demonstrated expertise in developing and implementing machine learning modelsProgramming skills in languages, tools and frameworks commonly used in data scienceExperience in data preprocessing and feature engineeringComputer science skills to support the overall development of the data science serviceFluent EnglishUK Driving LicenceYou're comfortable working well in teams or independently ...

uplift modelling capabilities across the team. Key Skills (Essential): To excel in this role, you should possess: Python Expertise: Strong experience in model development, feature engineering, and statistical modelling. SQL Proficiency: Confident in extracting and transforming large datasets effectively. Credit-Risk Modelling Experience: Proven track record in building ...

partner with 1,000+ clients.What you will be doingAs a Junior Software Engineer in our London office, your role will encompass:working on engineering projects together with senior team memberstraining and certification to enhance your skills in software engineering, data science, and data architecture.QualificationsNecessary education and experienceEducation … Bachelor's or Master’s degree in Computer Science, Mathematics, Statistics, Physics, Engineering, or a related quantitative field.Programming Proficiency: Strong programming skills in Python and a solid understanding of data structures and algorithms.Software Engineering Fundamentals: A demonstrable understanding of version control and repository tools (Git, CI/ ...

exceptional MSc) in ML, Computer Science, or related field.Deep theoretical and practical knowledge of core ML algorithms, and comfortable experimenting with model architectures, feature engineering, and hyperparameter tuning to produce high-performance and resilient models.Proven experience taking ML models from research to live production.For more information about ...