6 of 6 Permanent Feature Engineering Jobs in the UK excluding London

at its core their platform uses machine learning to turn business insights into business success. As a Machine Learning Engineer, you'll sit at the intersection of data science, engineering, and commercial strategy, working closely with our product and core engineering teams to translate business challenges into deployable ML solutions. You'll have the autonomy to experiment, iterate … gained working In a mission focussed, product led business. In return this ML Engineer will receive extensive growth and personal development opportunities as the business transitions away from legacy engineering practices. This ML Engineer based near Birmingham should have most of the following key skills: - Demonstrated experience delivering business impact and growth through ML solution design and development - Proven … experience in Python, TensorFlow/PyTorch, and modern ML frameworks. - Strong background in data modelling, feature engineering, and model deployment. - Experience with SQL, cloud platforms (AWS/GCP/Azure), and API integration. - A commercial mindset - you think in terms of ROI, not just model accuracy. - Excellent communication skills with the ability to influence non-technical stakeholders. - Experience More ❯

customer behaviours (e.g., lifetime value, acquisition efficiency), providing critical insights to our marketing and commercial teams. Own the complete development lifecycle for your machine learning models, from data gathering, feature engineering, and POC to model training, validation, and production deployment. Partner with our Machine Learning and Software Engineering teams to deploy your models as scalable, reliable, and More ❯

Engineer/Data Modeller role offers the chance to make a significant impact within an innovative, tech-driven organisation. You'll work at the forefront of data modelling, analytics engineering, and AI-enablement, helping shape scalable data products that power enterprise reporting, machine learning, and self-service insights. Senior Analytics Engineer/Data Modeller Responsibilities Design, build, and maintain … learning. Ensure documentation, governance, and data consistency across domains. Collaborate with data engineers to support robust ETL/ELT pipelines and maintain end-to-end data lineage. Deploy analytics engineering solutions using dbt, SQL transformations, and CI/CD best practice. Partner with analysts and data scientists to deliver performant and reliable datasets. Implement data quality monitoring, validation processes … and performance optimisation. Support AI initiatives by designing AI marts, feature engineering structures, and ML-ready datasets. Contribute to standardised KPIs, metadata, and a single source of truth for reporting. Work with business teams to translate complex requirements into scalable, high-impact models. Support agile delivery of data products and continuous improvement of modelling standards. Senior Analytics Engineer More ❯

Scientist to lead the development and application of advanced analytics and machine learning techniques that answer complex business questions and drive strategic decisions. You'll work closely with data engineering and business teams to design models and analytical solutions that improve customer experience, optimise operations, and support financial and strategic planning.This role combines technical expertise with leadership responsibilities, including … Mentor team members, present insights clearly to technical and non-technical audiences, and ensure best practices in analytical workflows. Technical Delivery: Engineer and optimise analytical and spatial SQL, build feature enrichment pipelines, develop and evaluate ML models, and package outputs for deployment. What You'll Need to Succeed Strong experience in applied machine learning (regression, tree ensembles, experiment design … . Advanced proficiency in Python and SQL, with experience in spatial SQL and PostGIS. Familiarity with spatial tools and libraries (GeoPandas, QGIS) and feature engineering concepts. Experience with data modelling, dbt, and version control (Git). Knowledge of spatial datasets (MasterMap, AddressBase, Land Registry). Desired: Experience with WMS/WFS services, graph theory (NetworkX), GDAL, and Snowflake. More ❯

the structure and purpose of their outputs and determine the most effective ways to visualise and communicate them. Data Product Development Support the development of robust data pipelines and feature engineering activities in partnership with Data Engineers. Design and develop a unified, user-friendly front-end interface that integrates dashboards, reports, models, and pipeline outputs into a single … or equivalent). Solid understanding of UX principles and accessibility standards (WCAG 2.2). Ability to collaborate with multidisciplinary teams and communicate complex information effectively. Desirable Experience with data engineering concepts such as pipelines, orchestration, or feature engineering. Familiarity with component-driven design systems. Knowledge of performance optimisation techniques for front-end applications. Experience working in Agile or More ❯

hands-on environment. Key Responsibilities: 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 to translate data into impact. Stay More ❯