4 of 4 Remote Feature Engineering Jobs in Central London

Full-time | Hybrid Join a tech consultancy at the forefront of applied AI—helping global brands design and deploy intelligent systems that solve real business problems. They combine deep engineering know-how with domain expertise to build the data infrastructure that powers machine learning and generative AI at scale. 🔍 About the Role As a Lead Data Engineer , you’ll … platforms using tools like Databricks , Airflow , Snowflake , and Spark Collaborate with AI/ML teams to align data processing with model requirements Develop ETL/ELT workflows to support feature engineering, model training, and inference Optimise data workflows for scalability, reliability, and cost-efficiency Ensure security, compliance, and data governance standards (e.g. GDPR , RBAC) Mentor junior engineers and More ❯

drive innovation into the product development process. You will interpret your client’s objectives, desires, and preferences to help the wider technical team understand the opportunities and apply data engineering responsibilities consistently. You will be working on an interesting range of projects that deliver to National Security customers and as such, you will have to hold the highest level … of UK Security Vetting (DV), upon application. Key Responsibilities: You will blend Data Engineering and Data Science, and will have experience that might cover a number of the tasks listed below: Data Engineering tasks Manage the implementation and development of integrations between the data warehouse and other systems. Create deployable data pipelines that are tested and robust using … Research, analyse and apply data sets using a variety of statistical and machine learning techniques. Support the analytical needs of the technical team inclusive of cleansing, mapping, statistical inferences, feature engineering and the bespoke data visualisation methods required by each project. Review the execution of software solutions and how these perform for the business and your clients, establishing More ❯

markets. Responsibilities: Lead the development and maintenance of credit risk and affordability models using bureau, open banking, and alternative behavioural data. Own end-to-end model lifecycle: data sourcing, feature engineering, model development, validation, and monitoring. Design and execute champion/challenger tests and A/B experiments to continuously improve approval rates, loss rates, and customer experience … performance data to generate actionable insight and support strategic decisions Mentor and develop a small team of analysts/data scientists as the team scales Work closely with Data Engineering to deploy models into production pipelines. Collaborate with stakeholders to define modelling goals and interpret model outcomes in a business context. Requirements: MSc or PhD Degree in Computer Science More ❯

in a technically rich environment. What You’ll Do Develop and deploy machine learning models including classification, regression, and clustering Work across the full model lifecycle: data prep, EDA, feature engineering, training, evaluation, and scaling Build predictive and propensity models for underwriting and claims Apply NLP and OCR for document classification and summarisation Collaborate with clients and cross More ❯