9 of 9 Permanent Feature Engineering Jobs in the UK excluding London

systems, contributing to projects that have immediate business impact. Key Responsibilities Collaborate with senior engineers and data scientists to build ML/AI models. Perform data wrangling, cleaning, and feature engineering on varied datasets. Help deploy machine learning pipelines and support integration into production. Evaluate model performance and suggest improvements. Keep up with advancements in AI/ML More ❯

and gain exposure to a wide range of tools, including cloud-based AI/ML platforms. What you'll do: Support development and optimisation of ML models through EDA, feature engineering, and testing Assist with data labelling, wrangling, validation, and governance Collaborate with stakeholders to deliver analytical insights and AI-driven solutions Use Python, SQL, and cloud-based More ❯

success criteria. Support and mentor junior team members, fostering a collaborative environment. Independently manage client relationships and project expectations. Develop and deploy ML models, applying innovative approaches beyond basic feature engineering. Use Python, SQL, and Tableau for reporting and analysis within an AWS environment. Work closely with Data Engineering, Sales, and Market Research teams across the UK, US … meaningful insights to drive business decisions. Strong communication skills, with experience in managing client relationships. A degree in a relevant field such as Mathematics, Statistics, Economics, Psychology, Sociology, Physics, Engineering, or Computer Science (Master’s or PhD is a plus). Interest or experience in TV viewing data, media, or marketing analytics is beneficial but not essential. If this More ❯

customer data, understanding and appreciating the underlying domain, carrying out analysis, and integrating or developing new techniques for implementation and delivery as part of our product offerings. This includes feature engineering, applying varying models, testing, and validation, and best practices for use for customers. Responsibilities: Development of predictive models using time series, geospatial and environmental sensor data. Designing … scalable feature engineering and data transformation processes tailored to sewer data. Collaboration with wastewater domain experts to guide bespoke modelling approaches to address industry issues. Build required product and custom features while seeking to maximise reuse of existing code and features. Engaging with customers to understand contextual requirements of projects, present findings and lead integration into StormHarvester product. … AI principles and application in implementation and practical delivery. Experienced in Python development and tooling including Pandas, Scikit-learn or equivalent. A third level qualification in Computer Science, Software Engineering, Data Science or other related discipline. Experience with data exploration and visualisation. A theoretical and practical foundation of core analytics and machine learning principles and experience working with large More ❯

improve and automate decision making Collaborate with technical and non-technical teams to understand problems, explore data, and develop effective fraud prevention tools and solutions Design and maintain robust feature engineering pipelines for modelling, working closely with analytics engineering teams Contribute to the development of end-to-end machine learning workflows and help embed models into production … heavily imbalanced datasets Excellent skills in Python and SQL Solid understanding of classification algorithms such as gradient boosting decision trees, including pros and cons of different model architectures Strong feature engineering skills and experience in transforming raw data into useful model inputs Effective communication skills and able to explain complex findings clearly to both technical and non-technical More ❯

improve and automate decision making Collaborate with technical and non-technical teams to understand problems, explore data, and develop effective fraud prevention tools and solutions Design and maintain robust feature engineering pipelines for modelling, working closely with analytics engineering teams Contribute to the development of end-to-end machine learning workflows and help embed models into production … heavily imbalanced datasets Excellent skills in Python and SQL Solid understanding of classification algorithms such as gradient boosting decision trees, including pros and cons of different model architectures Strong feature engineering skills and experience in transforming raw data into useful model inputs Effective communication skills and able to explain complex findings clearly to both technical and non-technical More ❯

and a clear path for continued growth, they are now hiring a Data Engineer to support their next generation of products and data initiatives. Reporting to the VP of Engineering Operations, this role will focus on building scalable data systems and integrating machine learning workflows that drive real-time personalisation and business insights across a high-traffic platform. Key … Responsibilities Design, build, and maintain robust data pipelines (batch and real-time)* Integrate and monitor machine learning models within live data workflows* Collaborate with Engineering, Product, and Analytics to ensure data accessibility and reliability* Optimise data infrastructure and automate manual processes* Uphold data integrity with strong validation and testing practices* Drive improvements in data delivery, observability, and internal tooling … cross-functional teams in leveraging data for decision-making Ideal Candidate Strong proficiency in Python and SQL for data wrangling and automation* Experience with ML workflows, model deployment, and feature engineering* Familiarity with modern data platforms (e.g., BigQuery, dbt, Looker)* Understanding of data modelling and cloud-based infrastructure (AWS or GCP)* Comfortable working in a fast-paced, product More ❯

with a strong analytical background, capable of maintaining technical contributions while managing a team. Your qualifications include: Experience delivering data science initiatives from concept to production, including data preprocessing, feature engineering, and model evaluation. Strong communication skills for explaining complex concepts to business stakeholders. Proficiency in Python or similar tools, strong SQL skills, and experience with data visualization More ❯

z2bz0 years Data Science experience. 2-3+ years Insurance Pricing domain knowledge. Experience with developing Machine Learning models. Using Machine Learning techniques to create business solutions. Knowledge of feature engineering and selection techniques. Coding experience in Python. Stakeholder engagement and interaction. A natural problem-solver. Model monitoring & maintenance. Mentoring and/or management of other team members. More ❯