1 to 25 of 74 Feature Engineering Jobs in England

fairer credit system. The Role We're looking for an experienced MLOps Engineer for a 3-month contract to lead the development of our ML deployment, testing, monitoring, and feature engineering pipelines . You'll be responsible for establishing best practices and production-grade systems to support our machine learning workflows from training to deployment and beyond. The … pipeline using AWS , with a strong focus on SageMaker for training, deployment, and hosting. - Integrate and operationalize MLflow for model versioning, experiment tracking, and reproducibility. - Architect and implement a feature store strategy for consistent, discoverable, and reusable features across training and inference environments (e.g., using SageMaker Feature Store , Feast, or custom implementation). - Work closely with data scientists … to formalize feature engineering workflows , ensuring traceability, scalability, and maintainability of features. - Develop unit, integration, and data validation tests for models and features to ensure stability and quality. - Establish model monitoring and alerting frameworks for real-time and batch inference (e.g., model drift detection, performance degradation). - Build CI/CD pipelines for ML workflows (training, evaluation, deployment More ❯

Engineering Manager, Machine Learning Platform London We're on a mission to make money work for everyone. We're waving goodbye to the complicated and confusing ways of traditional banking. With our hot coral cards and get-paid-early feature, combined with financial education on social media and our award winning customer service, we have a long history … solve problems and change lives through Monzo ️ London or Remote (UK) Base salary for this role is £110,500 - £145,000 (depending on experience) + stock options + Benefits Engineering Manager, Machine Learning Platform Engineering Management at Monzo: Engineering Managers at Monzo are part of cross-functional, autonomous teams and groups. Our teams are mission driven, and … groups, and then collectives - we aim to keep our line management structure as shallow as possible, and for teams to directly own decision making relevant to their work. The Engineering Manager role at Monzo is split into three pillars - people, product, and technical leadership. Engineering Managers are accountable for the technical and delivery outcomes for their area - that More ❯

Engineering Manager, Machine Learning Platform London We're on a mission to make money work for everyone. We're waving goodbye to the complicated and confusing ways of traditional banking. With our hot coral cards and get-paid-early feature, combined with financial education on social media and our award winning customer service, we have a long history … solve problems and change lives through Monzo ️ London or Remote (UK) Base salary for this role is £110,500 - £145,000 (depending on experience) + stock options + Benefits Engineering Manager, Machine Learning Platform Engineering Management at Monzo: Engineering Managers at Monzo are part of cross-functional, autonomous teams and groups. Our teams are mission driven, and … groups, and then collectives - we aim to keep our line management structure as shallow as possible, and for teams to directly own decision making relevant to their work. The Engineering Manager role at Monzo is split into three pillars - people, product, and technical leadership. Engineering Managers are accountable for the technical and delivery outcomes for their area - that More ❯

production. We work closely with stakeholders across the business to expand the understanding and impact of machine learning and AI throughout Trainline. We are looking for a Machine Learning Engineering Manager to join our team help shape the future of train travel. You will be part of a highly innovative AI and ML platform working alongside engineers, scientists and … opportunity to work with fellow ML enthusiasts on large-scale production systems, delivering highly impactful products that make a difference to our millions of users. As a Machine Learning Engineering Manager at Trainline you will Lead a high performing team of Machine Learning Engineers working alongside Software Engineers, Data Scientists, Data Engineers and Product Managers Ensure delivery of high … quality machine learning models and AI Systems at scale that drive measurable impact for our business Own the full end to end machine learning delivery lifecycle including data exploration, feature engineering, model selection and tuning, offline and online evaluation, deployments and maintenance Partner with stakeholders to propose innovative data products that leverage Trainline's extensive datasets and state 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 deliver NLP based machine learning systems at scale that drive measurable impact for our business Own the full end to end machine learning delivery lifecycle including data exploration, feature engineering, model selection and tuning, offline and online evaluation, deployments and maintenance Partner with stakeholders to propose innovative data products that leverage Trainline's extensive datasets and state … and platforms like ML Flow Have experience with agile delivery methodologies and CI/CD processes and tools Have a broad of understanding of data extraction, data manipulation and feature engineering techniques Are familiar with statistical methodologies. Have good communication skills Nice to have Experience with LangGraph or LangChain Experience with transport industry and/or geographical information More ❯

Responsibilities Lead the design, development, and maintenance of credit risk and affordability models using bureau, open banking, and behavioural data Own the full model lifecycle from data sourcing and feature engineering to validation, deployment, and monitoring Design and run A/B and champion/challenger tests to improve performance across approval rates, losses, and customer experience Analyse … credit performance data to deliver insights that guide strategic decisions Mentor and support junior analysts/data scientists as the team expands Collaborate with data engineering to deploy models into production Work closely with stakeholders to define goals, communicate findings, and translate model outputs into business value About You You are an analytical thinker with a passion for using … data to drive credit decisioning. You bring hands-on experience building machine learning models for consumer credit and understand the nuances of data preparation, feature selection, and model validation in high-stakes environments. 5–7 years of experience in a credit-related data science or decision science role Proficiency in Python and experience with libraries such as scikit-learn More ❯

Responsibilities Lead the design, development, and maintenance of credit risk and affordability models using bureau, open banking, and behavioural data Own the full model lifecycle from data sourcing and feature engineering to validation, deployment, and monitoring Design and run A/B and champion/challenger tests to improve performance across approval rates, losses, and customer experience Analyse … credit performance data to deliver insights that guide strategic decisions Mentor and support junior analysts/data scientists as the team expands Collaborate with data engineering to deploy models into production Work closely with stakeholders to define goals, communicate findings, and translate model outputs into business value About You You are an analytical thinker with a passion for using … data to drive credit decisioning. You bring hands-on experience building machine learning models for consumer credit and understand the nuances of data preparation, feature selection, and model validation in high-stakes environments. 5–7 years of experience in a credit-related data science or decision science role Proficiency in Python and experience with libraries such as scikit-learn More ❯

Responsibilities Lead the design, development, and maintenance of credit risk and affordability models using bureau, open banking, and behavioural data Own the full model lifecycle from data sourcing and feature engineering to validation, deployment, and monitoring Design and run A/B and champion/challenger tests to improve performance across approval rates, losses, and customer experience Analyse … credit performance data to deliver insights that guide strategic decisions Mentor and support junior analysts/data scientists as the team expands Collaborate with data engineering to deploy models into production Work closely with stakeholders to define goals, communicate findings, and translate model outputs into business value About You You are an analytical thinker with a passion for using … data to drive credit decisioning. You bring hands-on experience building machine learning models for consumer credit and understand the nuances of data preparation, feature selection, and model validation in high-stakes environments. 5–7 years of experience in a credit-related data science or decision science role Proficiency in Python and experience with libraries such as scikit-learn More ❯

Responsibilities Lead the design, development, and maintenance of credit risk and affordability models using bureau, open banking, and behavioural data Own the full model lifecycle from data sourcing and feature engineering to validation, deployment, and monitoring Design and run A/B and champion/challenger tests to improve performance across approval rates, losses, and customer experience Analyse … credit performance data to deliver insights that guide strategic decisions Mentor and support junior analysts/data scientists as the team expands Collaborate with data engineering to deploy models into production Work closely with stakeholders to define goals, communicate findings, and translate model outputs into business value About You You are an analytical thinker with a passion for using … data to drive credit decisioning. You bring hands-on experience building machine learning models for consumer credit and understand the nuances of data preparation, feature selection, and model validation in high-stakes environments. 5–7 years of experience in a credit-related data science or decision science role Proficiency in Python and experience with libraries such as scikit-learn More ❯

plays a crucial role in this journey, working on cutting-edge projects that enhance our digital presence and improve customer engagement. As a Senior AI Engineer within the Technology Engineering team in CIO, you will play a pivotal role in designing, developing, and deploying AI and machine learning solutions that address real-world business challenges. You will work closely … with cross-functional teams-including Data Science, Engineering, Product, and Business stakeholders-to identify opportunities for AI innovation and deliver scalable, ethical, and high-impact solutions. You will contribute to the Centre of Excellence for AI Engineering, support the adoption of GenAIOps practices, and help embed responsible AI principles across the development lifecycle. You'll also mentor junior … engineers, promote reusability of AI components, and support the continuous improvement of AI engineering practices across the organisation. Skills we would love you to have: Experience in AI/ML engineering or applied machine learning. Proficiency in Python and ML libraries (e.g. Semantic Kernel, Langchain, agentic frameworks). Experience deploying models using APIs, containers, or cloud-native services. More ❯

Aimpoint Digital is a premier analytics consulting firm with a mission to drive business value for clients through expertise in data strategy, data analytics, decision sciences, and data engineering and infrastructure. This position is within our decision sciences practice which focuses on delivering solutions via machine learning and statistical modelling. What you will do As a part of Aimpoint … Become a trusted advisor working with clients to design end-to-end analytical solutions Work independently to solve complex data science use-cases across various industries Design and develop feature engineering pipelines, build ML & AI infrastructure, deploy models, and orchestrate advanced analytical insights Write code in SQL, Python, and Spark following software engineering best practices Collaborate with … impact for your clients and do so through thoughtfulness, prioritization, and seeing a solution through from brainstorming to deployment. In particular you have these traits: Degree in Computer Science, Engineering, Mathematics, or equivalent experience. Experience with building high quality Data Science models to solve a client's business problems Experience with managing stakeholders and collaborating with customers Strong written More ❯

We work closely with stakeholders across the business to expand the understanding and impact of machine learning and AI throughout Trainline. The Role We are looking for a MLOps Engineering Manager to join our team and help shape the future of train travel. You will be part of a highly innovative AI and ML team working alongside engineers, scientists … the opportunity to work with fellow ML enthusiasts on large-scale production systems, delivering highly impactful products that make a difference to our millions of users. As a MLOps Engineering Manager at Trainline you will Build a new team of MLOps Engineers working alongside ML Engineers, Data Engineers, Software Engineers, Data Scientists and Product Managers Define MLOps processes and … machine learning products Ensure delivery of high-quality, scalable and maintainable machine learning models and AI Systems that drive measurable impact for our business Act as a bridge between engineering and data, ensuring engineering standards are met while understanding the specificities of data, AI and machine learning challenges Take an active part in our AI and ML community More ❯

and visibility functionality. As a senior member of the team, you'll be self motivated and be able to take ownership of projects, collaborate closely with stakeholders across product, engineering, and business to deliver data science solutions. Responsibilities Work across and support a range of data use cases including analytics and data provisioning Lead the design, development, and deployment … models and advanced analytics solutions to support recommendation and insight to production use cases Apply statistical techniques to extract insights and support data-driven decision-making Work alongside data engineering in requirements for data pipelines and feature engineering Promote best practices in data science, model validation, documentation, and reproducibility Qualifications Experience Strong coding skills in Python, including More ❯

ll Bring: We are seeking a seasoned professional who is excited by the unique challenges of AI data. Qualifications What are we looking for? Must-Have Skills: Extensive Data Engineering Experience: Proven track record (3+ years) in designing, building, and maintaining large-scale data pipelines and data warehousing solutions. Cloud Platform Mastery: Expert-level proficiency with at least one … data technologies like Apache Spark, Kafka, and data orchestration tools such as Apache Airflow or Prefect. ML Data Acumen: Solid understanding of data requirements for machine learning models, including feature engineering, data validation, and dataset versioning. Vector Database Experience: Practical experience working with vector databases (e.g., Pinecone, Milvus, Chroma) for embedding storage and retrieval. Generative AI Familiarity: Understanding … TensorFlow for data preparation in an ML context. Experience with real-time data streaming architectures. Familiarity with containerization (Docker, Kubernetes). Master's or Ph.D. in Computer Science, Data Engineering, or a related quantitative field. Additional Information Starcom has fantastic benefits on offer to all of our employees. In addition to the classics,Pension,Life Assurance, Private Medical and More ❯

requirements, data governance, and validation frameworks. Technology Leadership for AI Solutions: Provide senior technical and management oversight for technology teams specializing in AI/ML model development, MLOps, data engineering, and the integration of AI components into production systems. Ensure scalable, robust, and performant AI architectures. AI Integration & Innovation: Drive the identification, evaluation, and strategic integration of state-of … Translate complex AI concepts into understandable business value propositions and technical requirements. Data Strategy & Management for AI: Oversee the data strategy crucial for AI initiatives, including data acquisition, cleansing, feature engineering, and ensuring data quality and accessibility for model training and inference. Resource & Budget Management: Strategically manage resources, allocate budget, and plan financial oversight for high-priority AI … definition, and go-to-market execution. Technology Leadership: Prior experience providing senior-level oversight or direct management of technology teams, particularly those focused on AI/ML development, data engineering, or quantitative analysis. Data Fluency: Strong understanding of data architectures, big data technologies, and data governance practices essential for enterprise-level AI deployments. Analytical & Problem-Solving: Exceptional analytical, quantitative More ❯

predictive models, and solutions using a range of model types-from small statistical approaches to large language models (LLMs)-that streamline processes and improve decision-making. You will apply engineering best practice to move rapidly from concept to production, ensuring every solution is ethical, fair, explainable, and compliant. Thriving in a collaborative environment, you will work closely with stakeholders … languages such as Java, JavaScript/TypeScript, or C++ is beneficial, but your core expertise is in the Python ecosystem Skilled in core Data Science practices including data preprocessing, feature engineering, model evaluation, data orchestration, and data structures, etc Hands-on with AIOps/MLOps/ModelOps tooling (Docker, Kubernetes, MLflow, model monitoring, CI/CD) Experience integrating More ❯

comfortable supporting (or willing to learn) in the following areas: Programming for Data Science (e.g., Python with Pandas, NumPy, R) Statistical Analysis and Hypothesis Testing Data Cleaning, Preprocessing, and Feature Engineering Data Visualization (e.g., Matplotlib, Seaborn, Plotly, Tableau) Machine Learning Fundamentals (e.g., Supervised, Unsupervised Learning) Machine Learning Algorithms (e.g., Regression, Classification, Clustering, Decision Trees, SVMs, Neural Networks) Model More ❯

comfortable supporting (or willing to learn) in the following areas: Programming for Data Science (e.g., Python with Pandas, NumPy, R) Statistical Analysis and Hypothesis Testing Data Cleaning, Preprocessing, and Feature Engineering Data Visualization (e.g., Matplotlib, Seaborn, Plotly, Tableau) Machine Learning Fundamentals (e.g., Supervised, Unsupervised Learning) Machine Learning Algorithms (e.g., Regression, Classification, Clustering, Decision Trees, SVMs, Neural Networks) Model More ❯

comfortable supporting (or willing to learn) in the following areas: Programming for Data Science (e.g., Python with Pandas, NumPy, R) Statistical Analysis and Hypothesis Testing Data Cleaning, Preprocessing, and Feature Engineering Data Visualization (e.g., Matplotlib, Seaborn, Plotly, Tableau) Machine Learning Fundamentals (e.g., Supervised, Unsupervised Learning) Machine Learning Algorithms (e.g., Regression, Classification, Clustering, Decision Trees, SVMs, Neural Networks) Model More ❯

/CD pipelines and automated deployment practices. Familiarity with DevOps concepts, including containerization (e.g., Docker), orchestration (e.g., Kubernetes), and cloud infrastructure management (AWS, Azure, GCP). Experience in data engineering within Big Data ecosystems, including data pipelines and data integration. Solid understanding of software architecture and system design for high-availability applications. Knowledge of fundamental computer science concepts, including … maintain high-quality software development processes. Stay updated on the latest technologies and apply innovative solutions where applicable. Nice-to-Have Responsibilities (ML Focus): Develop, refine, and utilize ML engineering platforms and components as needed. Establish and manage processes for data preparation, feature engineering, and prediction. Closely monitor model performance and address any issues that arise. Explore More ❯

platforms (GCP preferred, AWS and Azure acceptable) Familiarity with Python ML packages such as PyTorch, TensorFlow, XGBoost, scikit-learn, SciPy, NumPy, pandas Strong SQL skills for data preparation and feature engineering Knowledge of MLOps principles, including automated retraining, monitoring, and deployment strategies Basic understanding of containerization and tools like Docker Nice-to-have skills: Experience with Google Cloud 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 ❯

machine learning and deep learning models. Contribute to scalable and reusable data pipelines using modern ML workflows. Conduct experiments and benchmarking exercises to test model performance. Perform error analysis, feature importance, and other model diagnostics. Track and log training/testing outcomes to support reproducibility and model versioning. Engineering Contributions Help build and integrate AI-powered APIs, scripts … tools, and containerization (e.g., Docker) to maintain codebase quality. Applied AI Domains Work on projects involving Natural Language Processing (NLP), Computer Vision, Generative AI, or Recommendation Systems. Support annotation, feature engineering, and augmentation tasks where necessary. Write clear, well-organized documentation for code, models, datasets, and workflows. Participate in team meetings, sprint planning, and code reviews. Engage with … to reflect on progress, set learning goals, and track outcomes. Required Qualifications A Bachelor's or Master's degree (completed or ongoing) in Computer Science, Data Science, Mathematics, Software Engineering, or a related STEM field. Eligibility to enroll in a Level 6 or Level 7 AI/ML/Data Science apprenticeship programme. Core Skills & Competencies Technical Skills Programming More ❯