15 of 15 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 ❯

innovation and leadership, this is the role you’ve been waiting for. Join a fast-growing Tech for Good Marketplace as their new ML Engineering Leader , where you’ll be at the forefront of AI-driven product development, building a skilled team, and driving the ML | Data Science | AI … vision for the business. What You'll Do: Develop and lead the ML Engineering | AI strategy as the company looks to drive a new period of experimentation & innovation with a personalised customer experience at the forefront of their plans. Lead and grow a team of ML engineers, fostering a … with software engineers, product managers, and business teams to define ML-driven solutions. Stay up-to-date with advancements in ML, AI, and data engineering best practices. Drive best practices in model explainability, bias mitigation, and ethical AI principles. What We’re Looking For: 5+ years of experience in 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 ❯

Proficient in Python programming and SQL, with experience in production-level code and data analysis libraries. · Familiar with ML Ops, model development workflows, and feature engineering techniques. · Capable of manipulating data and developing models accessible for business use, with experience in Azure AI Search. · Adept with software development More ❯

Proficient in Python programming and SQL, with experience in production-level code and data analysis libraries. Familiar with ML Ops, model development workflows, and feature engineering techniques. Capable of manipulating data and developing models accessible for business use, with experience in Azure AI Search. Adept with software development 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 ❯

for High-Frequency Strong proficiency in Python , C++, or other relevant languages. Deep understanding of AI and machine learning algorithms , including time series modeling, feature engineering, and model interpretability. Experience with market microstructure , order book dynamics, and execution strategies. Background in quantitative research , algorithmic trading, or data science. 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 ❯

solve business challenges. Collect, clean, and preprocess large datasets to ensure accuracy and reliability. Implement and fine-tune machine learning models, optimizing performance through feature engineering. Work with programming languages such as Python, Java, or Scala to build and deploy solutions. Analyze and interpret model results, providing insights and … You’ll Need: 1 to 7 years of experience in data science, AI, or machine learning. A Master’s or PhD in Computer Science, Engineering, Mathematics, Statistics, Physics, or a related field. Strong proficiency in machine learning techniques, including model training, testing, and feature selection. Experience with big 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 ❯

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 More ❯