17 of 17 Permanent 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 ...

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 ...

Location: Surrey, UK ( Office based ) Details: Full-Time | Truly competitive salary + Bonus + unrivalled benefits A global software company is evolving its core engineering platforms by embedding machine learning and applied AI into high-performance simulation and modelling tools used worldwide. This is a hands-on applied … role — focused on building and deploying ML solutions inside production-grade engineering systems, not isolated research or experimental prototypes. The position: You’ll design, build, and deploy machine learning models that directly enhance complex engineering software products. Expect a blend of ML engineering, software development, and computational ...

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 ...

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. ...

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 ...

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. ...

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 ...

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 ...