18 of 18 Permanent 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 ...

positioned to help shape the future of streaming. Continued success relies on building customer relationships with Roku that delight and engage them. Within Advertising Engineering, the MarTech team builds the products, services, and machine learning systems that help Roku deliver the right communication, creative, and marketing experience … pair a global mindset with locally relevant execution. You should be a gritty problem solver and self-starter who can work effectively with engineering, product, data science, and commercial stakeholders across Roku. The successful candidate will display a balance of hard and soft skills, including the ability to respond ...

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 ...

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 ...

practices across the function Design and deploy machine learning models across forecasting, customer segmentation, and propensity modelling Own end-to-end model development including feature engineering, validation, deployment, and monitoring Partner with Engineering and Product teams to build scalable, production-ready data science solutions Translate analytical outputs ...

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 ...

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 ...

ensuring high-quality, scalable model delivery across fraud and transaction monitoring use cases. Driveend-to-end model lifecycle ownership — from data exploration and feature engineering to deployment, monitoring, and performance optimisation. Provide hands-on technical leadership, reviewing Python code, model design, distributed computing approaches, and architectural decisions. Manage ...

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 ...

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 ...

typically lead a team or the solution delivery effort, demonstrating technical excellence through leading by example. You could be providing technical support, leading an engineering team or working across multiple teams as a subject matter expert who is critical to the success of a large programme of work. Your … deployments. Shape team behaviour for writing specifications and acceptance criteria, estimating stories, sprint planning and documentation. Actively define and evolve PA’s data engineering standards and practices, ensuring we maintain a shared, modern and robust approach. Lead and influence technical discussions with client stakeholders to achieve the collective ...

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 … need to understand how data, models, and trading systems interact. You can work productively with quants and understand what they need from the engineering side. You are senior enough to take ownership. CTO wants people he can hand large initiatives to and trust the output. 6 to 15+ years ...