14 of 14 Feature Engineering Jobs in the UK excluding London

Machine Learning, Artificial Intelligence, Predictive Analytics, Statistical Modelling, Python, SQL, PySpark, Azure, Databricks, MLflow, GitHub Actions, CI/CD, Time Series Forecasting, Propensity Modelling, Feature Engineering, Data Engineering, Azure Machine Learning, Azure Data Platform, Experiment Design, A/B Testing, Hypothesis Testing, Predictive Modelling, Customer Analytics, Marketing … that improve customer outcomes, enhance commercial performance & support strategic business decision making. Own the complete analytical lifecycle, from initial problem definition & exploratory analysis through feature engineering, model development, deployment, operational monitoring & continuous optimisation. Build sophisticated statistical & machine learning models covering areas such as: * Customer Lifetime Value * Customer Propensity ...

systems: devices that operate autonomously, make decisions in real time, and remain reliable under the constraints that define actual field deployment. The Challenge The engineering challenge is significant. You will be responsible for the complete lifecycle of machine learning models that run on embedded devices. This means: From Sensor … transform this stream into a robust, real-time classification model that runs on hardware with severe constraints on memory, computation, and power. Engineering Under Constraint. Every machine learning decision you make has downstream consequences for embedded systems. A model that requires 512MB of RAM will ...

committed to advancing tools that are needed to transform healthcare in the future. The Institute brings together researchers in life and physical sciences, and engineering, to develop a spectrum of tools which we will use to image, interpret and intervene in biological systems. These insights will speed … multi-scale image resolutions. The work may also involve applying topological data analysis (TDA) to assist with the design, construction and deployment of new feature engineering and optimisation strategies for the machine-learning (ML) modelling of cellular data. More generally, this role offers a great opportunity ...

committed to advancing tools that are needed to transform healthcare in the future. The Institute brings together researchers in life and physical sciences, and engineering, to develop a spectrum of tools which we will use to image, interpret and intervene in biological systems. These insights will speed … multi-scale image resolutions. The work may also involve applying topological data analysis (TDA) to assist with the design, construction and deployment of new feature engineering and optimisation strategies for the machine-learning (ML) modelling of cellular data. More generally, this role offers a great opportunity ...

across health and safety, sustainability and ethical behaviour. As a Data Scientist, you'll join a growing, highly skilled team spanning data science, data engineering, AI engineering and DevOps. You'll play a key role in building and deploying machine learning and AI solutions that power business applications … Models, with the chance to integrate innovative AI capabilities including LLMs, MCPs, APIs and enterprise data into production platforms. You'll work closely with Engineering and Product teams in a collaborative Agile environment, turning complex data and technology into solutions that deliver tangible business value. The role will include ...

Senior AI Software Engineer, you will play a key role in designing, developing, and implementing intelligent software solutions that drive innovation, improve engineering productivity, and deliver measurable business value. You will work closely with AI Architects, Data Engineers, Data Scientists, Product teams, and Engineering colleagues to build scalable … Generative AI, AI-assisted code generation, automated testing, code review acceleration, agentic workflows, and development process optimisation. This role involves providing technical leadership, engineering expertise, and tooling oversight across the software delivery lifecycle, helping teams apply AI responsibly to modernise platforms, improve code quality, streamline delivery, and enhance developer ...

concept into production environments Develop scalable ML pipelines using AWS cloud technologies Implement MLOps and LLMOps best practices for deployment, monitoring and governance Support feature engineering, model optimisation and performance monitoring Apply responsible AI principles, including model explainability and fairness Present findings and recommendations to technical … tools such as MLflow, Weights & Biases or Data Version Control Experience designing, testing and evaluating machine learning experiments Knowledge of Generative AI, LLMs, prompt engineering and RAG architectures Experience with LLMOps tools such as LangChain, LangSmith or LangGraph Strong understanding of model monitoring, validation and governance Excellent communication ...

Lead the development, implementation, and end-to-end delivery of advanced machine learning models and algorithms to drive market operations initiatives. Partner with AI Engineering teams to ensure robust architecture design and deployment patterns for AI/ML models that align with business needs. Mentor and guide a team … managing the machine learning lifecycle. Proficiency in Python and machine learning frameworks such as PyTorch, TensorFlow, and scikit-learn. Strong understanding of data preprocessing, feature engineering, and evaluation techniques. Experience working with large, complex datasets and applying statistical analysis. Familiarity with cloud platforms (AWS, Azure, GCP) and containerization ...

research-only environment. You'll work on real business problems, build machine learning models that drive decision-making, and collaborate closely with engineering teams to see your work deployed and used at scale. What you'll be doing: Partnering with stakeholders to turn business challenges into Data Science solutions … looking for: Commercial experience as a Data Scientist Strong Python and SQL skills Hands-on experience building Machine Learning models Expertise in feature engineering, model evaluation and model selection Experience working with large datasets Exposure to Azure, AWS or GCP Strong stakeholder management and communication skills Experience taking ...

Data Science team of a large, established financial services business. The company has invested in its data platform and is building a dedicated ML Engineering capability to get more models into production. You'll work on real business problems, using large and varied datasets to develop models that … initial experimentation. You should be comfortable with: Python and common data science libraries. SQL and working with large datasets. Statistical modelling and machine learning. Feature engineering, model selection and evaluation. Writing clear, maintainable and testable code. Git-based development workflows. Working in a cloud environment such as Azure ...

risk of mental health problems prior to first contact with services. The role is highly collaborative and will involve close working with clinical, engineering, and operational colleagues across CADRE's partner institutions, as well as with academic and NHS co-investigators. Although employed by Cambridgeshire and Peterborough NHS Foundation … attached job description and person specification for full details of responsibilities. Working with data prepared and quality-assured by the CADRE data engineering team, the postholder will contribute to longitudinal analyses of the cohort, including: Describing the cohort at index event (first contact with health, education, or social care ...

driven choices made through the analysis of actuarial experience, profitability drivers, trends and capital requirements. Working alongside Actuarial, Data Science, Business Intelligence and Data Engineering teams, the position focuses on developing and enhancing analytical models, data processes and insights that help deliver scalable solutions and drive commercial value across … business. Key Actions Support the ownership, maintenance and continuous development of actuarial data assets, including feature engineering processes and experience analysis models used across the Life business Analyse lapse, claims, retention and business mix experience to identify trends, monitor performance and provide insights that support strategic decision making ...

doing Develop and deploy ML and statistical models across credit risk, affordability and pricing Own models end-to-end, including data, feature engineering, modelling, validation, deployment and monitoring Build model monitoring frameworks and performance dashboards Explore new data sources, challenger models and A/B testing to improve ...

uplift modelling capabilities across the team. Key Skills (Essential): To excel in this role, you should possess: Python Expertise: Strong experience in model development, feature engineering, and statistical modelling. SQL Proficiency: Confident in extracting and transforming large datasets effectively. Credit-Risk Modelling Experience: Proven track record in building ...