16 of 16 Feature Engineering Jobs in England

monitoring processes Build a framework that supports the creation, deployment, maintenance, and monitoring elements that non-data scientist and machine learning analysts produce, including assisting with hyper-parameter tuning, feature engineering, feature selection, and validation, reporting and visualisation, and communication processes. Work closely with the data science team to integrate modelling approaches and techniques Key Skills and More ❯

engineering. Design and implement AI-powered solutions, leveraging Python, SQL/NoSQL, and APIs for seamless integration. Prototype and rigorously test AI applications, focusing on improving performance through strategic feature engineering and model optimization. Engage with the latest open-source AI/ML tools to enhance business solutions continuously. Develop, deploy, and manage machine learning models aimed at … of various ML algorithms including supervised, unsupervised, and deep learning. Strong problem-solving and effective communication skills. Qualifications: Bachelors or Masters degree in Computer Science, Data Science, Machine Learning, Engineering, or related field. Benefits: 25 days annual leave plus bank holidays Performance-based bonus scheme linked to individual, team, and company achievements Generous Defined Contribution Pension scheme Permanent Health More ❯

data and AI strategy scales effectively, directly influencing the way millions of people engage with their products every day. The Opportunity This is a unique chance to combine data engineering with machine learning in a high-impact environment. You'll work closely with analysts, data engineers and stakeholders, ensuring models are reliable, scalable, and production-ready. Unlike many roles … work applied at scale, powering decision-making and user experiences for a vast audience. Your day-to-day will include: Building and maintaining end-to-end data pipelines and feature engineering workflows. Deploying and monitoring ML models in production using tools such as MLflow, Vertex AI, or Azure ML. Driving best practices in MLOps, including CI/CD … gym access. Access to wellbeing support services and employee assistance programmes. Clear career progression and opportunities to work with cutting-edge tech. Skills and Experience Degree in Computer Science, Engineering, Mathematics, or a related field. Proven experience in data or ML engineering. Strong knowledge of Python and SQL. Hands-on experience with cloud platforms (GCP or Azure) and Databricks. More ❯

Key Skills Proficiency in Python and/or R for developing machine learning models. Experience with frameworks such as TensorFlow, PyTorch, or Scikit-learn. Strong understanding of data preprocessing, feature engineering, and model evaluation techniques. Familiarity with cloud platforms like AWS, GCP, or Azure for deploying ML solutions. Knowledge of version control systems (e.g., Git) and CI/ More ❯

across the organization. Responsibilities Understand business problems and conduct statistical analysis independently. Break down hard problems. Communicate effectively to senior stakeholders. Deliver value end-to-end. Self-serve data engineering and infrastructure as required. Make recommendations on best practice in terms of analysis, machine learning and data science. Have a transformative presence in the team. Develop and implement machine … learning models, including feature engineering, model design, training, and deployment. Perform data mining, exploration, and statistical analysis to uncover trends and actionable insights. Create data visualizations, reports, dashboards, and perform data audits. Leverage predictive models to optimize customer experiences and drive business outcomes. Create automated anomaly detection systems to monitor and ensure data quality and operational performance. Qualifications … Computer Science, or a related field. Doctorate in a quantitative field such as Statistics, Computer Science, Mathematics, or Engineering. A "full stack" data scientist - with extensive expertise of data engineering, analysis and analytics, as well as machine learning. 6+ years of experience working in Data Science, preferably within a Software organization. Experience with financial fraud detection and prevention is More ❯

relevance. Build production-ready Python code and integrate models into user-facing applications. Monitor and refine model performance post-deployment, making improvements based on feedback. Collaborate with product and engineering teams to deliver solutions aligned with business goals. Role Requirements 2-4 years' experience in applied machine learning and generative AI, including work with large language models. Strong Python … core ML libraries (numpy, pandas, scikit-learn, boosting methods). Proven ability to design, test, and deploy production-ready machine learning solutions. Hands-on experience in data processing and feature engineering for complex datasets. A degree in Computer Science, Statistics, Machine Learning, Engineering, Physics, or a related quantitative field. More ❯

and product managers, to deliver robust AI solutions. Key Skills Proficiency in Python, TensorFlow, or PyTorch Experience with machine learning algorithms and frameworks Strong understanding of data pre-processing, feature engineering, and model evaluation Familiarity with cloud services (AWS, GCP, Azure) and their AI/ML offerings Knowledge of natural language processing (NLP) and computer vision is a More ❯

the lead on projects that improve the core discovery experience-such as personalisation, relevance ranking, and multi-modal retrieval-as well as conduct deep investigations into user behaviour and feature performance. You'll be working across the full research and experimentation lifecycle: from framing the problem and exploring the data, to prototyping models, running offline evaluations, and validating ideas … technical direction Qualifications 5+ years of experience in applied data science, preferably in search, recommendations or user modelling Strong Python and SQL skills, with deep experience in data exploration, feature engineering and model evaluation Proven experience applying and comparing models for structured prediction, ranking, retrieval or recommendation Strong understanding of offline evaluation techniques and trade-offs in information … retrieval and recommender systems Ability to communicate clearly across disciplines and seniority levels-including product, design and engineering Experience planning and delivering projects end-to-end, from problem definition to experimentation and rollout Familiarity with AB testing design and analysis in online product settings Bonus: experience working with embeddings (e.g. image, text, product), vector search, LLMs or hybrid models More ❯

in this journey, working on cutting-edge projects that enhance our digital presence and improve customer engagement. As a Principal AI Engineer, you will be part of the Technology Engineering team within CIO, leading the design, development, and deployment of advanced AI and machine learning solutions that drive innovation, efficiency, and strategic value across the organisation. You will collaborate … closely with cross-functional teams, including Data Science, Engineering, Product, and Business stakeholders, to understand complex business challenges and identify opportunities where AI can deliver measurable impact. You will lead the end-to-end lifecycle of AI initiatives - from problem framing and data exploration to model development, deployment, and monitoring - ensuring solutions are scalable, ethical, and aligned with enterprise … goals. Skills we would love you to have: Extensive experience in AI/ML engineering, data science, or applied machine learning roles. Proven track record of delivering production-grade AI solutions in complex, data-rich environments. Proficiency in Python and key ML libraries (e.g. Semantic Kernel, Langchain and Agentic frameworks). Experience deploying models into production using APIs, containers More ❯

build out new analytics products for claims and underwriting Execute data analysis and exploratory analysis (project design, processing of and cleaning of data, merging/joining disparate data sources, feature engineering, performing analyses and communicating results). Produce models using a variety of algorithms (GLM, GBM, Random Forest, Neural Networks etc.) and assess the relative strength of each More ❯

to drive innovation into the product development process. You will interpret your clients objectives, desires, and preferences to help the wider technical team understand the opportunities and apply data engineering responsibilities consistently. You will be working on an interesting range of projects that deliver to National Security customers and as such, you will have to hold the highest level … of UK Security Vetting (DV), upon application. Key Responsibilities: You will blend Data Engineering and Data Science, and will have experience that might cover a number of the tasks listed below: Data Engineering tasks Manage the implementation and development of integrations between the data warehouse and other systems. Create deployable data pipelines that are tested and robust using … Research, analyse and apply data sets using a variety of statistical and machine learning techniques. Support the analytical needs of the technical team inclusive of cleansing, mapping, statistical inferences, feature engineering and the bespoke data visualisation methods required by each project. Review the execution of software solutions and how these perform for the business and your clients, establishing More ❯

ethical deployment of AI technologies, ensuring strict adherence to data privacy standards and regulations. What we are looking for: A university degree in Computer Science, Data Science, Artificial Intelligence, Engineering, or a related field. Proven experience in designing, developing, and deploying machine learning models and AI algorithms. Strong proficiency in programming languages such as Python, R, or Java. Solid … understanding of data processing, feature engineering, and data analytics. Ability to collaborate effectively with cross-functional teams including data scientists, engineers, and product managers. Strong problem-solving skills with attention to detail and the ability to handle complex datasets. Knowledge of data privacy standards, ethical AI practices, and regulatory compliance. Why you will love working with us Competitive More ❯

months. Technical Skills Machine Learning & Deep Learning Supervised/unsupervised/reinforcement learning Model selection, training, validation, and evaluation Deep learning architectures (CNNs, RNNs, Transformers) Data Science Statistical analysis, feature engineering, A/B testing Experiment design and hypothesis testing MLOps & Engineering Scalable ML systems (batch and real-time) ML pipelines, CI/CD, monitoring, deployment Familiarity More ❯

models and solutions. The AI Engineer will:· Design and implement AI-powered solutions· Work with Python, SQL/NoSQL, and APIs for integration· Test AI applications· Improve performance through feature engineering· Explore and incorporate the latest open-source AI/ML tools into business solutions· Develop and deploy machine learning models · Solve business problems· Clearly communicate technical ideas … in API development/integrationAbility to analyze model performance In return our client offers outstanding benefits and a great working environment. Please apply for more opportunity on this AI Engineering position. More ❯

via RESTful APIs or cloud-native platforms (e.g., Azure, AWS). Ensure high availability and fault tolerance of AI services in production environments. Build robust data pipelines for preprocessing, feature engineering, and real-time inference. Set up monitoring tools to track model performance, drift, and system health. Iterate quickly based on feedback, usage metrics, and evolving business needs. More ❯

request, investigate, identify relevant data sources, and prototype a solution testing the outputs by querying the data whilst identifying questions to further clarify. Qualifications Experts in SQL and SQL feature engineering on Google Cloud Platform (GCP)/Household 360, with familiarity in windowed functions, nested queries, query optimisation and complex ETL/ELT patterns. Experience working in Big More ❯