1 to 25 of 27 Feature Engineering Jobs in the UK excluding London

models by converting analysts' Python code into scalable, maintainable and deployable workflows Design, build and maintain data pipelines for pricing inputs, including ingestion, transformation, feature preparation and quality checks Build and automate workflows for elasticity, forecasting, optimisation and other pricing models Develop and manage API integrations, including competitor pricing … feeds and downstream systems Work closely with pricing analysts to translate pricing logic into production-ready processes Support model performance improvement through data preparation, feature engineering and data mining techniques Monitor production processes and model performance over time, recommending corrective action where required Ensure pricing models are deployed ...

Data Scientist | Cardiff/Hybrid | Engineering | AI & Predictive Analytics We're supporting a growing engineering business looking to hire a Data Scientist to help develop scalable ML and AI solutions across compliance, risk and contractor analytics platforms. You'll work closely with AI Engineers, Data Engineers and DevOps … learning initiatives that directly support operational performance, compliance and risk management. You'll be involved in the full model lifecycle from data ingestion and feature engineering through to deployment, optimisation and monitoring. Key Responsibilities Develop machine learning models for risk scoring, churn prediction and contractor analytics Build ...

hire has very meaningful impact.They are looking for a Senior Data Scientist to lead the predictive analytics capability and their critical programme.You’ll design feature engineering pipelines, select and validate classification and regression models, and establish rigorous evaluation methodology (targeting AUC-ROC 0.85) across a 300M+ point education … explainable and production-ready.Core Responsibilities: Predictive Model Development : Build and validate supervised learning models (classification & regression) using complex, multi-source, time-series-influenced data. Feature Engineering : Design scalable feature pipelines across attendance, behaviour, wellbeing, assessment and SEND datasets. Evaluation & Methodology : Establish rigorous evaluation frameworks including ...

Trust. Using Databricks as the primary development environment, you will build reproducible, auditable analytical workflows in SQL and Python, including data preparation, quality checks, feature engineering and modelling. You will also design and deliver reporting products and dashboards (for example in Power BI) to communicate clear, actionable insight … analytical and predictive models on curated Trust datasets. This includes full responsibility for data preparation activities such as data quality checks, cleansing, preprocessing and feature engineering, ensuring all work follows agreed definitions and is reproducible and auditable. The postholder will create reporting products and dashboards (for example using ...

systems that process high-volume, high-value data and increasingly leverage AI and automation to deliver measurable customer and business outcomes. We value pragmatic engineering, clear thinking, and continuous learning. Our teams are small, autonomous, and outcome-focused, with a strong emphasis on quality, ownership, and collaboration. … platform scalability, operational excellence and maturity, and cost-efficient growth to support our long-term strategy and enterprise ambitions. The Role AI Platform Architecture & Engineering Own the design, build, and evolution of Infinity’s AI platform - the infrastructure layer that underpins AI-driven product capability and AI-assisted engineering ...

features, model selection, architecture decisions Conduct exploratory data analysis and communicate insights Collaborate with data engineers, architects, and business analysts on integrated solutions Build feature engineering pipelines and automated data preparation workflows Design AI solutions for commercial transformation including pricing optimization, customer segmentation, and revenue management Develop scalable … proposals and technical assessments for new opportunities and internal knowledge transfer Essential Qualifications Degree or equivalent certification in Computer Science, Data Science, Statistics, Mathematics, Engineering, or related quantitative field Proven experience building and implementing LLM-based solutions (GPT, Claude, Llama, Mistral, or similar) Hands‐on experience with at least ...

solutions and regulatory reporting — ensuring teams across the business can trust and use data with confidence. You’ll collaborate closely with colleagues in Data Engineering, Data Science, Pricing, Platform Engineering and MLOps, acting as a trusted partner and technical authority. Together, you’ll define clear standards … self‐service analytics and AI/ML model consumption. Collaborate with ML Ops and Data Science teams to define data product standards and feature engineering patterns. Evaluate and lead adoption of emerging Azure and Databricks capabilities — including Microsoft Fabric, OneLake and DirectLake — where they advance the data architecture. ...

solutions and regulatory reporting — ensuring teams across the business can trust and use data with confidence. You’ll collaborate closely with colleagues in Data Engineering, Data Science, Pricing, Platform Engineering and MLOps, acting as a trusted partner and technical authority. Together, you’ll define clear standards … self‐service analytics and AI/ML model consumption. Collaborate with ML Ops and Data Science teams to define data product standards and feature engineering patterns. Evaluate and lead adoption of emerging Azure and Databricks capabilities — including Microsoft Fabric, OneLake and DirectLake — where they advance the data architecture. ...

deploying scalable machine learning models that drive data-driven decision-making across the business. This role bridges the gap between data science and software engineering, turning prototypes into production-ready systems. Key Responsibilities Design, develop, and deploy machine learning models and pipelines in production environments Collaborate with data scientists … software engineers, and stakeholders to translate business requirements into ML solutions Optimize model performance, scalability, and reliability Build and maintain data pipelines and feature engineering workflows Monitor and retrain models to ensure continued performance over time Implement best practices for version control, testing, and CI/ ...

experience designing, building, and optimizing data solutions that enable advanced analytics and AI-driven business transformation. This role requires expertise in modern data engineering practices, cloud platforms, and the ability to deliver robust, scalable data pipelines for diverse business domains such as finance, supply chain, energy, and commercial operations. … data storage, retrieval, and processing for performance and scalability on cloud platforms (Azure, AWS, GCP, Databricks, Snowflake). Translate business requirements into technical data engineering solutions, including architecture decisions and technology selection. Contribute to proposals, technical assessments, and internal knowledge sharing. Data preparation, feature engineering, and MLOps ...

priorities. Identify high-value ML use cases and translate commercial problems into scalable analytical solutions. Lead end-to-end model lifecycle delivery: problem framing, feature engineering, experimentation, validation, deployment, monitoring, and iteration. Establish best practices for experimentation, evaluation, reproducibility, and documentation. Set standards for model governance, explainability, monitoring … financial environment. Machine Learning & Delivery Architect and develop robust ML models (e.g., classification, regression, anomaly detection) using Python and cloud-based tooling. Design scalable feature pipelines in collaboration with Data Engineering. Lead productionisation efforts, including pipeline design, model versioning, and monitoring frameworks. Implement safe deployment strategies (e.g., champion/ ...

logistic regression, gradient boosting, random forests, clustering, NLP Proficient in Python and/or R, with strong experience in data quality, model development and feature engineering Strong command of SQL and familiarity with data engineering environments such as Databricks or similar Skilled in data visualisation and storytelling ...

Collaborate with data engineers, analysts, and product teams to translate business needs into AI-driven solutions Contribute to the development of data pipelines and feature engineering workflows Integrate models into production using APIs, batch jobs, or real-time systems Apply best practices around experimentation, evaluation, versioning, and monitoring ...

Senior Data Scientist to take a leading role across a portfolio of technically demanding projects. You’ll operate end-to-end - shaping problem definitions, engineering data pipelines, developing advanced models, and ensuring outputs are robust, explainable and deployable in real-world settings. This is a hands-on role … impact. Key Responsibilities Translating complex, ambiguous problem statements into clear, actionable data science solutions. Owning the full data science lifecycle, from data ingestion and feature engineering through to modelling, evaluation and deployment. Developing statistical, machine learning and deep learning models to support high-impact, real-world decision making. ...

deployment of ML-driven features in our core wastewater network platform focusing on predicting sewer behaviour. You will work within the Data & Modelling engineering team with a focus on improving our existing ML processes and designing and integrating new data-driven strategies into existing products to help add insight … customers. This role will be involved with (and lead) the development of a new ML-driven feature from ideation to proof of concept to deployment to integration with the product. This will involve: Gaining an understanding of the domain and existing StormHarvester product Exploratory data analysis and visualisation Conceptualising ...

problem definition through to deployment in live environments. * Design, build, and deploy machine learning models within Pega-based decisioning platforms. * Lead model development across feature engineering, training, validation, and ongoing performance monitoring. * Work closely with application and logic developers to embed models into operational decision workflows. * Develop statistical ...

emphasis is on refinement, optimisation and continuous improvement rather than building from scratch. You will be responsible for the intellectual core of the models: Feature engineering across financial, behavioural and transactional data Algorithm selection and tuning (logistic regression, gradient boosting, ensemble methods) Model validation, performance optimisation and ongoing … recalibration Ensuring models remain robust in changing economic conditions You will not be responsible for infrastructure, pipelines or deployment. A dedicated engineering team manages AWS and production environments, allowing you to focus on modelling and analytics. This is a highly visible role with direct exposure to senior stakeholders. ...

topics, including: Fundamentals of ML and AI (including Machine Learning Lifecycle, Machine Learning Mathematical Foundations); Solving Business Problems with Machine Learning; Data Preparation and Feature Engineering; Planning and preparing ML/AI solution; Data Ethics and Responsible AI; Model Engineering and Training; Model Evaluation and Deployment; Monitoring ...

topics, including: Fundamentals of ML and AI (including Machine Learning Lifecycle, Machine Learning Mathematical Foundations); Solving Business Problems with Machine Learning; Data Preparation and Feature Engineering; Planning and preparing ML/AI solution; Data Ethics and Responsible AI; Model Engineering and Training; Model Evaluation and Deployment; Monitoring ...

topics, including: Fundamentals of ML and AI (including Machine Learning Lifecycle, Machine Learning Mathematical Foundations); Solving Business Problems with Machine Learning; Data Preparation and Feature Engineering; Planning and preparing ML/AI solution; Data Ethics and Responsible AI; Model Engineering and Training; Model Evaluation and Deployment; Monitoring ...

topics, including: Fundamentals of ML and AI (including Machine Learning Lifecycle, Machine Learning Mathematical Foundations); Solving Business Problems with Machine Learning; Data Preparation and Feature Engineering; Planning and preparing ML/AI solution; Data Ethics and Responsible AI; Model Engineering and Training; Model Evaluation and Deployment; Monitoring ...

Must-haves 3+ years experience in data science Strong Python and SQL skills Experience building and evaluating predictive models Understanding of data modelling and feature engineering Ability to translate data into clear commercial insight and recommendations Confident communicator - comfortable working directly with clients Consultancy or client-facing experience ...

Must-haves 3+ years experience in data science Strong Python and SQL skills Experience building and evaluating predictive models Understanding of data modelling and feature engineering Ability to translate data into clear commercial insight and recommendations Confident communicator - comfortable working directly with clients Consultancy or client-facing experience ...

/DL models. Manage and maintain ML systems, libraries, and pipelines, ensuring robust deployment into production. Analyse diverse datasets to inform model architecture and feature engineering. Stay current with state‐of‐the‐art ML/DL research and evaluate new technologies for practical application. Mentor and guide junior ...

ownership and production-grade model deployment. The Role As Senior Data Scientist, you will: Own end-to-end ML solutions -from problem framing and feature engineering to deployment, monitoring, and governance Translate business objectives into modelling strategies aligned to risk appetite and operational constraints Build and deploy models … using Python, SQL, and AWS (SageMaker or equivalent) Partner closely with Engineering, Data, and Risk/Financial Crime teams to ensure robust, production-ready solutions Establish monitoring frameworks for performance, drift, and retraining Drive clear documentation, traceability, and governance appropriate for a regulated environment This role requires someone ...