16 of 16 Feature Engineering Jobs in the UK excluding London

RESPONSIBILITIES: In this role, you will be responsible for: Designing, developing, and deploying AI/ML models and solutions, including LLMs and GenAI. Performing feature engineering and selection to optimize model performance. Selecting and implementing appropriate AI/ML algorithms, including supervised, unsupervised, and reinforcement learning models. Training More ❯

as TensorFlow, PyTorch, or Scikit-learn. Expert-level experience in Power BI for advanced visualisations, ML model interpretation, and KPI tracking. Deep knowledge of feature engineering, model deployment, and MLOps best practices. Experience with big data processing (Spark, Hadoop) and cloud-based data science environments. Other: Ability to … integrate ML workflows into large-scale data pipelines. Strong experience in data preprocessing, feature selection, and statistical modelling. Experience communicating complex findings to both technical and non-technical stakeholders. If you are interested and looking for your next role, please apply directly or email . More ❯

as TensorFlow, PyTorch, or Scikit-learn. Expert-level experience in Power BI for advanced visualisations, ML model interpretation, and KPI tracking. Deep knowledge of feature engineering, model deployment, and MLOps best practices. Experience with big data processing (Spark, Hadoop) and cloud-based data science environments. Other: Ability to … integrate ML workflows into large-scale data pipelines. Strong experience in data preprocessing, feature selection, and statistical modelling. Experience communicating complex findings to both technical and non-technical stakeholders. If you are interested and looking for your next role, please apply directly or email (url removed More ❯

with world-class expertise in machine learning, statistics, optimization and stochastic control. These advisors include AI Labs co-head Stephen Boyd (Samsung Professor of Engineering at Stanford), Emmanuel Candes, Trevor Hastie, and Mykel Kochenderfer who dedicate time in our Palo Alto office and provide advice and guidance for all … problems. Build and maintain tools and services supporting the full model development lifecycle for statistical models, machine learning, optimization, and deep learning models (e.g., feature engineering, backtesting and simulation, validation, deployment). Maintain and monitor production models and experimentation. Tune performance in both single-threaded and distributed environments. … Enforce high-quality patterns and practices for maintaining model pipelines. Requirements 7+ years in software engineering, with 3+ years in API-backed ML deployment. Strong programming language skills in Python. Significant experience with SQL (e.g., RDBMS, Spark, Presto, or BigQuery). Experience with machine learning, optimization, and data manipulation More ❯

structures to other ESP modeling tools. Qualifications EXPERIENCE/QUALIFICATIONS/EDUCATION REQUIRED Educational Requirements Bachelor's and/or master's in electrical engineering, economics, mathematics, or a related quantitative field (data science or data engineering emphasis desired). Required Work Experience 3-5 years of experience … high-performance computing environments. Experience with extracting, transforming, and loading processes and tools for handling large-scale datasets. Demonstrated ability to develop and deploy Feature Engineering and Modeling applications to data platforms built on Databricks or similar platforms and platform components (e.g., Snowflake, ML Flow, Airflow, etc.). More ❯

delivering innovative, tailored data driven solutions combined with insight generation. Key responsibilities Advanced Analytics Delivery: Lead end‑to‑end data analytics projects—data exploration, feature engineering, model development (ML/AI), validation, and deployment—tailored to solving client business problems Analytics Framework & Playbooks: Co‑create repeatable playbooks for More ❯

across major client projects. THE ROLE As a Data Scientist, you will: Build and deploy machine learning solutions end-to-end, from SQL-based feature engineering to model development in Python and cloud deployment (AWS) Prototype and test new ideas that solve real business problems or spark client More ❯

training demos. ✅ What You’ll Work On: • Collaborate with senior data scientists on live projects • Assist in cleaning, organizing, and analyzing datasets • Contribute to feature engineering for machine learning models • Learn how A/B tests and data experiments are designed and analyzed • Help build dashboards or visualizations More ❯

training demos. ✅ What You’ll Work On: • Collaborate with senior data scientists on live projects • Assist in cleaning, organizing, and analyzing datasets • Contribute to feature engineering for machine learning models • Learn how A/B tests and data experiments are designed and analyzed • Help build dashboards or visualizations More ❯

training demos. ✅ What You’ll Work On: • Collaborate with senior data scientists on live projects • Assist in cleaning, organizing, and analyzing datasets • Contribute to feature engineering for machine learning models • Learn how A/B tests and data experiments are designed and analyzed • Help build dashboards or visualizations More ❯

training demos. ✅ What You’ll Work On: • Collaborate with senior data scientists on live projects • Assist in cleaning, organizing, and analyzing datasets • Contribute to feature engineering for machine learning models • Learn how A/B tests and data experiments are designed and analyzed • Help build dashboards or visualizations More ❯

training demos. ✅ What You’ll Work On: • Collaborate with senior data scientists on live projects • Assist in cleaning, organizing, and analyzing datasets • Contribute to feature engineering for machine learning models • Learn how A/B tests and data experiments are designed and analyzed • Help build dashboards or visualizations More ❯

training demos. ✅ What You’ll Work On: • Collaborate with senior data scientists on live projects • Assist in cleaning, organizing, and analyzing datasets • Contribute to feature engineering for machine learning models • Learn how A/B tests and data experiments are designed and analyzed • Help build dashboards or visualizations More ❯

training demos. What You’ll Work On: • Collaborate with senior data scientists on live projects • Assist in cleaning, organizing, and analyzing datasets • Contribute to feature engineering for machine learning models • Learn how A/B tests and data experiments are designed and analyzed • Help build dashboards or visualizations More ❯

Quantitative Developer | Systematic Research A high-performing global quant fund is scaling its Research Engineering function — and we're looking for a Quantitative Developer who's already familiar with the demands of a hedge fund or trading environment. You'll be embedded directly in the research process, working shoulder … to-shoulder with quants and PMs, building and owning the infra that powers alpha generation. What You’ll Actually Be Doing Engineering research tools in Python and C++ , built for scale and speed Designing systems to handle massive data ingestion , feature engineering, and backtesting Collaborating directly with … ll Need to Bring 5+ years in a systematic trading or quant research environment Fluency in Python and/or C++, with a strong engineering mindset Hands-on with distributed systems , data pipelines , or ML tooling Ability to partner with researchers without translation layers Comfortable with ownership, ambiguity, and More ❯

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 … 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 More ❯