11 of 11 Feature Engineering Jobs in the South East

Lead, Applied Scientist and Research Engineer positions—for upcoming roles across applied machine learning, generative AI, MLOps and model productionisation. These are hands-on engineering roles where you'll build, train, ship and operate the models that drive real product behaviour and real business outcomes. You'll work across … lifecycle—from problem framing and data preparation through to model development, evaluation, deployment, monitoring and iteration. The role suits someone who pairs solid software engineering foundations with genuine ML rigour and a healthy scepticism about what models can and can't be trusted to do. Key Responsibilities Partner with ...

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 ...

Leadership Own end-to-end architecture across data and AI layers: Data ingestion, processing, modelling, semantic layer, and consumption AI platform integration (model lifecycle, feature engineering, inference pipelines) Design modern Lakehouse + AI architecture leveraging Azure and Databricks Define architecture for scalable, governed, and reusable AI-ready data … lineage, security, and responsible AI principles 3. AI Platforms & AI-led Data Migration Design and implement AI Platforms integrating: Model development environments, MLOps pipelines, feature stores, and model serving Lead AI-driven migration strategies , including: Automated schema discovery, data mapping, and transformation using AI accelerators AI-assisted code conversion ...

Leadership Own end-to-end architecture across data and AI layers: Data ingestion, processing, modelling, semantic layer, and consumption AI platform integration (model lifecycle, feature engineering, inference pipelines) Design modern Lakehouse + AI architecture leveraging Azure and Databricks Define architecture for scalable, governed, and reusable AI-ready data … lineage, security, and responsible AI principles 3. AI Platforms & AI-led Data Migration Design and implement AI Platforms integrating: Model development environments, MLOps pipelines, feature stores, and model serving Lead AI-driven migration strategies , including: Automated schema discovery, data mapping, and transformation using AI accelerators AI-assisted code conversion ...

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 ...

audit requirements. Experience with GDPR and AI governance frameworks. Key responsibilities Build and deploy predictive and credit risk models. Lead exploratory data analysis, feature engineering, model validation and monitoring. Develop forecasting, simulation and stress-testing models. Work with data engineering teams to create modelling-ready datasets using ...

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. ...

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 ...

teams to align architecture with business objectives. Provide technical leadership and governance across AI work streams and delivery teams Drive best practice in AI engineering, model management, and data science operations Evaluate and select appropriate AI frameworks, tools, and cloud services to meet enterprise requirements Support the integration … systems Skills and Experience Proven experience delivering AI solutions at enterprise scale in production environments Strong background in Generative AI — including LLMs, prompt engineering, and model fine-tuning Hands-on experience with Hugging Face (model hub, Transformers, Inference API) Experience with AWS AI services (SageMaker, Bedrock, Rekognition, Comprehend ...

then scale into production Shape problem definitions with stakeholders in ambiguous environments Bring best practices from adjacent industries into a high-performance setting Data Engineering & Architecture Design/maintain pipelines integrating telemetry/timing, video/image, event operations, and digital/commercial engagement data Develop APIs/services … secure-by-design delivery with cyber teams What we're looking for Essentials 5-10 years' experience in data science/AI/ML engineering Strong Python Production ML deployment experience (end-to-end) Strong SQL + modern data warehouse experience Cloud familiarity + containerisation/orchestration Streaming data ...

Analyse datasets to identify patterns, trends, and actionable insights. Support the development and evaluation of machine-learning models. Assist with data cleaning, preparation, and feature engineering. Conduct statistical analysis to support business decisions. Build reports, dashboards, and visualisations for internal stakeholders. Collaborate with technical and non-technical teams ...

major growth phase and help build the firm's long-term technology platform.The company combines the stability of an established investment business with the engineering culture of a high-performing technology organization. Engineers work in small, highly autonomous teams with significant ownership over critical systems. Senior hires are expected … data to trading infrastructure, where speed and reliability are fundamental requirements Building integrated environments where quantitative researchers develop, test, and deploy predictive models - from feature engineering through execution Architecting cloud-based simulation and experimentation platforms that support large-scale quantitative research without becoming a bottleneck Standing up toolchains ...

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 ...