7 of 7 Remote/Hybrid Feature Engineering Jobs in London

Python and SQL skills Experience developing and deploying machine learning models into production environments Excellent understanding of statistical modelling, experimentation, and model evaluation Strong feature engineering and exploratory data analysis capabilities Experience communicating technical findings and insights to non-technical stakeholders A degree qualification (BSc, MSc, PhD etc. … innovation The Senior Data Scientist role will involve: Developing and deploying machine learning models to solve real-world business challenges Performing exploratory data analysis, feature engineering, model development, and evaluation Building forecasting, classification, segmentation, and predictive modelling solutions Designing and executing statistical analyses and experiments to support strategic ...

explainability, and performance evaluation Requirements Strong experience as a Senior Quant Data Scientist Deep understanding of: Regression, classification, and ranking models Time-series analysis & feature engineering Hands-on experience with: Python (pandas, NumPy, scikit-learn, etc.) Gradient boosting frameworks (XGBoost/LightGBM/CatBoost) Experience working with LLMs ...

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 ...

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 ...

advanced ranking models for Depop’s entire app, covering personalised recommendations, search results and other surfaces. Collaborate closely with cross-functional partners (product, engineering, data) to define problems, translate them into scalable solutions, and deliver measurable business outcomes. Lead the end-to-end lifecycle of ML projects: from ideation … data acquisition, feature engineering, training, and evaluation to deployment and ongoing iteration. Drive innovation in ranking by researching and integrating emerging ML techniques, frameworks, and tooling, while contributing technical expertise to long-term product and data strategy. Mentor, coach, and set technical direction within the Ranking ML team ...

models (e.g., clustering, regression, predictive analytics) with ability to take problems from framing through to deployment-ready outputs Must be strong in data exploration, feature engineering, model evaluation, and communicating insights clearly to non-technical stakeholders ideally within demand-led public services (predictive demand, prevention, triage/segmentation ...

will be responsible for designing, building, and governing predictive models that support data-driven products and strategic decision-making. You will work closely with engineering and product teams to transform raw data into robust, auditable, and commercially valuable solutions. Skills & Experience Technical Expertise Strong proficiency in Python (Pandas, NumPy … Snowflake or similar cloud-based data warehouse platforms. Experience using Git and reproducible development practices. Strong understanding of data pipelines, data quality, and analytics engineering principles. Credit Modelling & Predictive Analytics Proven experience conducting rigorous exploratory data analysis and feature engineering. Experience building predictive models in regulated financial services ...