12 of 12 Remote Feature Engineering Jobs in London

Purpose of Position We are looking for an Data Engineering Manager to lead our AI/ML and Data Science Team. As a Data Engineering Manager, you will lead and mentor a team of 6-12 Data Engineers, fostering collaboration, ownership, and continuous learning to drive the success of our Affiliate Marketing platform. Your role involves overseeing data … solution delivery, aligning engineering efforts with business objectives, and ensuring best practices across data engineering processes. Beyond day-to-day management, you will play a key role in recruitment, career development, and strategic growth while facilitating collaboration between squads, departments, and stakeholders. Key tasks: Lead, mentor, and manage a team of 6-12 Data Engineers, ensuring their growth … Data Engineers. Establish clear team ownership and promote a culture of autonomy, knowledge sharing, and continuous improvement. Oversee the delivery of data solutions, ensuring alignment with business goals and engineering best practices. Run performance and development review processes, setting and tracking individual development goals through regular 1:1s. Provide constructive feedback, resolve conflicts, and create a supportive team environment. More ❯

have an exciting opportunity for a Data Scientist to join our rapidly growing Sports Forecasting & Analytics company. Purpose of the role As a Data Scientist within the Modelling & Data Engineering department, you will play a key role in the design, development, and implementation of predictive models that power our sports forecasting products. You will work collaboratively within a sport … from large-scale sports datasets using sound mathematical and statistical principles. Translate modelling requirements and business objectives into effective data science solutions, working closely with the Delivery Manager and Engineering teammates (Software and Data Engineers) within your modelling team. Perform data cleaning, exploratory data analysis (EDA), feature engineering, and model evaluation to support continuous model improvement. Write … able to contribute to cross-functional discussions. Proven problem-solving and time management skills. Desirable: Familiarity with cloud services (e.g. AWS S3, Athena, Lambda). Basic understanding of data engineering or ML pipelines. Knowledge of distributed systems (e.g. Kafka). Interest in American sports or the betting industry. Some exposure to .NET-based systems or application integration. Follow our More ❯

have an exciting opportunity for a Data Scientist to join our rapidly growing Sports Forecasting & Analytics company. Purpose of the role As a Data Scientist within the Modelling & Data Engineering department, you will play a key role in the design, development, and implementation of predictive models that power our sports forecasting products. You will work collaboratively within a sport … from large-scale sports datasets using sound mathematical and statistical principles. Translate modelling requirements and business objectives into effective data science solutions, working closely with the Delivery Manager and Engineering teammates (Software and Data Engineers) within your modelling team. Perform data cleaning, exploratory data analysis (EDA), feature engineering, and model evaluation to support continuous model improvement. Write … able to contribute to cross-functional discussions. Proven problem-solving and time management skills. Desirable: Familiarity with cloud services (e.g. AWS S3, Athena, Lambda). Basic understanding of data engineering or ML pipelines. Knowledge of distributed systems (e.g. Kafka). Interest in American sports or the betting industry. Some exposure to .NET-based systems or application integration. Follow our More ❯

have an exciting opportunity for a Data Scientist to join our rapidly growing Sports Forecasting & Analytics company. Purpose of the role As a Data Scientist within the Modelling & Data Engineering department, you will play a key role in the design, development, and implementation of predictive models that power our sports forecasting products. You will work collaboratively within a sport … from large-scale sports datasets using sound mathematical and statistical principles. Translate modelling requirements and business objectives into effective data science solutions, working closely with the Delivery Manager and Engineering teammates (Software and Data Engineers) within your modelling team. Perform data cleaning, exploratory data analysis (EDA), feature engineering, and model evaluation to support continuous model improvement. Write … able to contribute to cross-functional discussions. Proven problem-solving and time management skills. Desirable: Familiarity with cloud services (e.g. AWS S3, Athena, Lambda). Basic understanding of data engineering or ML pipelines. Knowledge of distributed systems (e.g. Kafka). Interest in American sports or the betting industry. Some exposure to .NET-based systems or application integration. Follow our More ❯

have an exciting opportunity for a Data Scientist to join our rapidly growing Sports Forecasting & Analytics company. Purpose of the role As a Data Scientist within the Modelling & Data Engineering department, you will play a key role in the design, development, and implementation of predictive models that power our sports forecasting products. You will work collaboratively within a sport … from large-scale sports datasets using sound mathematical and statistical principles. Translate modelling requirements and business objectives into effective data science solutions, working closely with the Delivery Manager and Engineering teammates (Software and Data Engineers) within your modelling team. Perform data cleaning, exploratory data analysis (EDA), feature engineering, and model evaluation to support continuous model improvement. Write … able to contribute to cross-functional discussions. Proven problem-solving and time management skills. Desirable: Familiarity with cloud services (e.g. AWS S3, Athena, Lambda). Basic understanding of data engineering or ML pipelines. Knowledge of distributed systems (e.g. Kafka). Interest in American sports or the betting industry. Some exposure to .NET-based systems or application integration. Follow our More ❯

most. Connect to your opportunity We are seeking to hire experienced Lead GenAI System Architect(s) in the AI Institute, which is a centre of excellence in Deloitte's Engineering, AI & Data service offering. You will be working with clients and other third parties, as well as Deloitte teams from across the Firm. You will have the opportunity to … to shape, define, and deliver transformative AI and Generative AI strategies aligned with business goals. Lead the design, development, and implementation of advanced AI pipelines, encompassing data acquisition, preprocessing, feature engineering, model development, evaluation, and secure deployment at scale. Oversee the development and operationalisation of state-of-the-art AI models, including large language models (LLMs), diffusion models … experience in some of the following: Education & Experience PhD in Computer Science, Machine Learning, Artificial Intelligence, or a related discipline preferred. Outstanding candidates with strong quantitative, computer science, or engineering backgrounds in a related field will also be considered. Extensive experience designing, developing, and deploying enterprise-grade AI/ML solutions, including experience managing technical teams and stakeholder relationships. More ❯

Experience with common Python packages for Machine Learning - examples include PyTorch, TensorFlow, XGBoost, scikit-learn, SciPy, NumPy, pandas, etc. * Strong knowledge of SQL and its use for data preparation & feature engineering * Understanding of & practical experience with implementing MLOps principals - including automated model retraining, monitoring & deployment strategies * Some knowledge of containerisation & use of tools like Docker & Docker Compose Nice More ❯

at scale to help optimise product bidding and maximise profit across platforms like Google Shopping. Expect to work across the full ML lifecycle-from exploring large, messy datasets and engineering features, to evaluating models offline and running experiments to validate impact. At the same time, you'll build, deploy and monitor models in production: setting up retraining workflows, pipeline … clean, documented, well tested and reviewed code and have tooling and a culture to support this. This is a hands-on, high-impact role that blends research, experimentation and engineering, all tied to clear business outcomes. You'll collaborate closely with marketers, data analysts and engineers, and play a key part in shaping the future of how we scale … impact ad quality or model input 3+ years of experience building and deploying ML models in production Strong Python and SQL skills, with a solid understanding of data wrangling, feature engineering and model evaluation Deep understanding of the data science process-comfortable with exploratory analysis, statistical testing, and model comparison techniques Experience with structured prediction problems (e.g. regression More ❯

build out new analytics products for claims and underwriting Execute data analysis and exploratory analysis (project design, processing of and cleaning of data, merging/joining disparate data sources, feature engineering, performing analyses and communicating results). Produce models using a variety of algorithms (GLM, GBM, Random Forest, Neural Networks etc.) and assess the relative strength of each More ❯

to drive innovation into the product development process. You will interpret your clients 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 ❯

happy - by continuously training and deploying machine learning models. We aim to make model deployments as easy and error-free as code deployments. Google's Best Practices for ML Engineering is our bible. Our models are trained to spot multiple types of fraud, using a variety of data sources and techniques in real time. The prediction pipelines are under … it's down to the Detection team to investigate why. The Detection team is core to Ravelin's success. They work in a deeply collaborative partnership with the Data Engineering team to design the data architecture and infrastructure that powers our ML systems. This close alignment ensures our models are built on a foundation of high-quality, reliable, and … efficiently processed data. The Role We are looking for a Machine Learning Engineer to join our Detection team. You will be the crucial bridge between data science and engineering, responsible for productionising the cutting-edge models our data scientists develop. Your role is to build, scale, and maintain the robust, high-performance ML systems that form the core of More ❯

happy - by continuously training and deploying machine learning models. We aim to make model deployments as easy and error-free as code deployments. Google's Best Practices for ML Engineering is our bible. Our models are trained to spot multiple types of fraud, using a variety of data sources and techniques in real time. The prediction pipelines are under … it's down to the Detection team to investigate why. The Detection team is core to Ravelin's success. They work in a deeply collaborative partnership with the Data Engineering team to design the data architecture and infrastructure that powers our ML systems. The Role We are looking for a Senior Machine Learning Engineer to join our Detection team. … Beyond just consuming data, you will take a leading role in defining how data is modeled, stored, and served for machine learning purposes, directly influencing the architecture of our feature generation pipelines and ensuring data quality throughout the ML lifecycle. You'll take strategic ownership over several aspects of our ML infrastructure and be empowered to introduce and champion More ❯