1 to 25 of 27 Permanent Feature Engineering Jobs in England

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 ...

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 ...

deployment, and optimisation of machine learning models and analytical solutions. You will gain exposure across the full data science life cycle, including data exploration, feature engineering, model development, validation, and deployment. This role is well suited to someone with a solid foundation in data science who is looking …/or R. Experience using machine learning frameworks and libraries such as scikit-learn, TensorFlow, or PyTorch. Good understanding of statistics, data preparation, feature engineering, and exploratory data analysis. Strong problem-solving skills and the ability to communicate technical concepts effectively. Experience with data visualisation tools and libraries ...

taxonomies, citations, metadata, and content from every scientific discipline. Apply the right technique to each problem, using approaches such as classification, regression, clustering, ranking, feature engineering, deep learning, embeddings, LLMs, retrieval, and generative AI. Develop capabilities for semantic search, information retrieval, entity extraction, content classification, recommendation, ranking, summarization … inference, experimentation, monitoring, and continuous improvement. Support deployment, monitoring, model maintenance, drift detection, automated retraining, and ongoing optimization of data science systems. Collaborate with engineering, product, UX, analytics, research, and domain experts, and communicate technical concepts, model behavior, insights, trade-offs, and recommendations clearly to technical and non-technical ...

taxonomies, citations, metadata, and content from every scientific discipline. Apply the right technique to each problem, using approaches such as classification, regression, clustering, ranking, feature engineering, deep learning, embeddings, LLMs, retrieval, and generative AI. Develop capabilities for semantic search, information retrieval, entity extraction, content classification, recommendation, ranking, summarization … inference, experimentation, monitoring, and continuous improvement. Support deployment, monitoring, model maintenance, drift detection, automated retraining, and ongoing optimization of data science systems. Collaborate with engineering, product, UX, analytics, research, and domain experts, and communicate technical concepts, model behavior, insights, trade-offs, and recommendations clearly to technical and non-technical ...

position responsible for designing, building, and deploying enterprise-grade AI solutions that drive measurable business value across the organisation. Working closely with IT, Data, Engineering, and senior business stakeholders, you will lead the development and implementation of advanced AI solutions, leveraging Large Language Models (LLMs), Retrieval-Augmented Generation … expertise with strategic thinking, taking solutions from concept through to production deployment and adoption. The ideal candidate will have a strong foundation in AI Engineering combined with a robust Data Science background, enabling them to develop, evaluate, and optimise AI solutions that deliver measurable business outcomes. This role would ...

will be building and maintaining a cost efficient and scalable machine learning platform, that is a delight to use and that provides a good engineering and data science experience while shortening the full experimentation feedback loop - a data scientist does not just deploy models fast, but learns fast which … Products & Insights Squad. We own the infrastructure layer that sits between data scientists and production: model serving, training pipelines, model registry and experiment tracking, feature management, and model monitoring on the line. Our customers are internal - Data Scientists and ML engineers across Wise - and our success is measured ...

offer . About the role: Join us as a Software Engineer in our critical Trust and Safety team. This is a high-impact engineering role with a strong product focus, dedicated to solving complex, real-world adversarial problems to directly protect our global customer base. How we work … securing customers' money, accelerating product growth by raising automation levels, and helping us engineer a world-class money transfer product. What do you need? Engineering Expertise: Professional experience with Java or other JVM-based languages, including the Spring framework. System Design & Operation: Proven experience designing and operating CI/ ...

home 100% of the time. Your Role: Implement and finetune generative AI models under the guidance of senior team members Contribute to prompt engineering and development of Ai powered workflows Assist with the deployment monitoring and maintenance of AI models in production environments Collaborate with data scientists and engineers … ensure seamless integration of AI capabilities Perform data preprocessing feature engineering and API development for AI applications Participate in code reviews testing and documentation to ensure quality and reliability Stay updated with advancements in GenAI and share relevant learnings with the team Required Technical Skills Handson experience with ...

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/ ...

understanding of JDBC and database internals. Experience with CI/CD pipelines and Distributed and Concurrent Systems Experience with machine learning basics (data pipelines, feature engineering, recall/precision, familiarity with machine learning systems in production) is a huge plus A strong product mindset and passion for user … work – a practical guide DEI @ Wise Wise Tech Stack (2025 update) See what it's like to work at Wise London! Our Engineering career map Wise Engineering – https://medium.com/wise-engineering What do we offer: Starting salary: £87,500 - £111,000 + RSUs Wise ...

queries and manage remediation actions and findings Your skills and experience Advanced degree (Master’s or PhD) in a quantitative discipline (e.g., Mathematics, Physics, Engineering, Computer Science) 7+ years’ experience developing analytical or machine learning models in financial services (ideally Anti-Financial Crime/Screening) Experience building Natural Language … Processing (NLP)/Machine Learning (ML)/Artificial Intelligence (AI) pipelines, including feature engineering, model training, evaluation and monitoring Experience designing evaluation frameworks for LLM use cases (e.g., human-in-the-loop, calibration, guardrails, auditability) Experience with hyperparameter tuning at scale and experimentation frameworks Strong technical experience with ...

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 ...

business goals Effective communication and collaboration skills, with demonstrated experience working across cross-functional teams Bachelor’s degree or higher in Computer Science, Software Engineering, or a related field. As a Software Engineer specializing in AI systems, you will play a key role in designing and implementing production-grade … agents using techniques such as retrieval-augmented generation, prompt optimization, fine-tuning, and reinforcement learning Develop end-to-end pipelines for data ingestion, feature engineering, model inference (batch and real-time), and integration of AI-driven workflows into production systems Collaborate with data scientists and machine learning engineers ...

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. ...

Responsibilitie sPerform exploratory data analysis (EDA) to uncover trends, anomalies, and opportunitie sDevelop and validate machine learning models (regression, classification, clustering, etc. )Conduct feature engineering, hypothesis testing, and model evaluatio nTranslate business requirements into data science use cases and analytical solution sDeliver actionable insights to drive optimisation, efficiency ...

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 ...

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 ...

optimization techniques for LLM-based agents Resource-constrained AI model deployment Vector databases and semantic search (e.g., Pinecone, Weaviate, Milvus, Qdrant , and ChromaDB ) Prompt engineering for efficient agent reasoning LLM fine-tuning and instruction optimization Graph databases for network topology and context management Feature engineering for network … deliver end-to-end services and solutions with our deep industry expertise and strong partner ecosystem, leveraging our capabilities across strategy, technology, design, engineering and business operations. The Group reported 2025 global revenues of €22.5 billion. Make it real | www.capgemini.com ...

that reflect risk assessment outcomes and model performance. Qualifications A bit about you: Proven track record of deploying models from scratch, including data preprocessing, feature engineering, model selection, evaluation, and monitoring. Strong Python knowledge. Ability to read through code, especially Java. Demonstrable experience collaborating with engineering ...

build scalable forecasting systems that continuously generate, deploy and improve predictive models. You'll work with large-scale data, applying machine learning, experimentation and feature engineering to improve prediction accuracy and drive better customer outcomes. You'll also help shape product strategy, establish data science best practices ...