1 to 25 of 40 Permanent Feature Engineering Jobs in England

Location: dmg media HQ - High Street Kensington, London, W8 Position: Permanent About the Role We are seeking a motivated ML Engineer/Data Engineer to join our Data Engineering team and help evolve our data and machine learning platforms. In this role, you'll work at the intersection of machine learning and data engineering - designing and maintaining scalable … solving complex problems with data and machine learning. Main Responsibilities Collaborate with data analysts to create ML models from prototype to production Design, build, and maintain data pipelines and feature engineering workflows Deploy, monitor, and optimize ML models and pipelines in production Implement MLOps best practices including CI/CD, experiment tracking, and model monitoring Support and evolve … governance across systems Contribute to building data-driven products that combine analytics and ML capabilities Skills & Expertise Required Bachelor's degree (Master's preferred) in Computer Science, Applied Mathematics, Engineering, or related field Professional experience in data engineering, ML engineering, or a related field Strong programming skills in Python and SQL Experience with Google Cloud Platform and More ❯

monitoring processes Build a framework that supports the creation, deployment, maintenance, and monitoring elements that non-data scientist and machine learning analysts produce, including assisting with hyper-parameter tuning, feature engineering, feature selection, and validation, reporting and visualisation, and communication processes. Work closely with the data science team to integrate modelling approaches and techniques Key Skills and More ❯

monitoring processes Build a framework that supports the creation, deployment, maintenance, and monitoring elements that non-data scientist and machine learning analysts produce, including assisting with hyper-parameter tuning, feature engineering, feature selection, and validation, reporting and visualisation, and communication processes. Work closely with the data science team to integrate modelling approaches and techniques Key Skills and 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 ❯

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 ❯

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 ❯

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 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 ❯

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 ❯

Key Skills Proficiency in Python and/or R for developing machine learning models. Experience with frameworks such as TensorFlow, PyTorch, or Scikit-learn. Strong understanding of data preprocessing, feature engineering, and model evaluation techniques. Familiarity with cloud platforms like AWS, GCP, or Azure for deploying ML solutions. Knowledge of version control systems (e.g., Git) and CI/ More ❯

across the organization. Responsibilities Understand business problems and conduct statistical analysis independently. Break down hard problems. Communicate effectively to senior stakeholders. Deliver value end-to-end. Self-serve data engineering and infrastructure as required. Make recommendations on best practice in terms of analysis, machine learning and data science. Have a transformative presence in the team. Develop and implement machine … learning models, including feature engineering, model design, training, and deployment. Perform data mining, exploration, and statistical analysis to uncover trends and actionable insights. Create data visualizations, reports, dashboards, and perform data audits. Leverage predictive models to optimize customer experiences and drive business outcomes. Create automated anomaly detection systems to monitor and ensure data quality and operational performance. Qualifications … Computer Science, or a related field. Doctorate in a quantitative field such as Statistics, Computer Science, Mathematics, or Engineering. A "full stack" data scientist - with extensive expertise of data engineering, analysis and analytics, as well as machine learning. 6+ years of experience working in Data Science, preferably within a Software organization. Experience with financial fraud detection and prevention is More ❯

relevance. Build production-ready Python code and integrate models into user-facing applications. Monitor and refine model performance post-deployment, making improvements based on feedback. Collaborate with product and engineering teams to deliver solutions aligned with business goals. Role Requirements 2-4 years' experience in applied machine learning and generative AI, including work with large language models. Strong Python … core ML libraries (numpy, pandas, scikit-learn, boosting methods). Proven ability to design, test, and deploy production-ready machine learning solutions. Hands-on experience in data processing and feature engineering for complex datasets. Solid understanding of machine learning algorithms and statistical modelling techniques. A degree in Computer Science, Statistics, Machine Learning, Engineering, Physics, or a related More ❯

relevance. Build production-ready Python code and integrate models into user-facing applications. Monitor and refine model performance post-deployment, making improvements based on feedback. Collaborate with product and engineering teams to deliver solutions aligned with business goals. Role Requirements 2-4 years' experience in applied machine learning and generative AI, including work with large language models. Strong Python … core ML libraries (numpy, pandas, scikit-learn, boosting methods). Proven ability to design, test, and deploy production-ready machine learning solutions. Hands-on experience in data processing and feature engineering for complex datasets. Solid understanding of machine learning algorithms and statistical modelling techniques. A degree in Computer Science, Statistics, Machine Learning, Engineering, Physics, or a related More ❯

and product managers, to deliver robust AI solutions. Key Skills Proficiency in Python, TensorFlow, or PyTorch Experience with machine learning algorithms and frameworks Strong understanding of data pre-processing, feature engineering, and model evaluation Familiarity with cloud services (AWS, GCP, Azure) and their AI/ML offerings Knowledge of natural language processing (NLP) and computer vision is a More ❯

science solutions that deliver commercial value Lead the design, development, and deployment of predictive and optimisation models across multiple industries Own the end-to-end ML pipeline: data exploration, feature engineering, modelling, evaluation, and deployment Collaborate with data engineers and MLOps professionals to ensure scalable, production-grade solutions Conduct rigorous A/B testing and performance measurement to … engineers, product leads, and client stakeholders Experience with A/B testing and causal inference methodologies Bachelor’s or Master’s degree in a quantitative field (e.g., Mathematics, Physics, Engineering, Computer Science) Excellent communication skills and a collaborative mindset Example Projects You Might Work On Optimisation models to increase manufacturing throughput Predictive models for asset maintenance and downtime reduction More ❯

science solutions that deliver commercial value Lead the design, development, and deployment of predictive and optimisation models across multiple industries Own the end-to-end ML pipeline: data exploration, feature engineering, modelling, evaluation, and deployment Collaborate with data engineers and MLOps professionals to ensure scalable, production-grade solutions Conduct rigorous A/B testing and performance measurement to … engineers, product leads, and client stakeholders Experience with A/B testing and causal inference methodologies Bachelor’s or Master’s degree in a quantitative field (e.g., Mathematics, Physics, Engineering, Computer Science) Excellent communication skills and a collaborative mindset Example Projects You Might Work On Optimisation models to increase manufacturing throughput Predictive models for asset maintenance and downtime reduction More ❯

real-world systems, contributing to projects that have immediate business impact. Key Responsibilities Collaborate with senior leadership team to build ML/AI models. Perform data wrangling, cleaning, and feature engineering on varied datasets. Help deploy machine learning pipelines and support integration into production. Evaluate model performance and suggest improvements. Keep up with advancements in AI/ML More ❯

real-world systems, contributing to projects that have immediate business impact. Key Responsibilities Collaborate with senior leadership team to build ML/AI models. Perform data wrangling, cleaning, and feature engineering on varied datasets. Help deploy machine learning pipelines and support integration into production. Evaluate model performance and suggest improvements. Keep up with advancements in AI/ML More ❯

in this journey, working on cutting-edge projects that enhance our digital presence and improve customer engagement. As a Principal AI Engineer, you will be part of the Technology Engineering team within CIO, leading the design, development, and deployment of advanced AI and machine learning solutions that drive innovation, efficiency, and strategic value across the organisation. You will collaborate … closely with cross-functional teams, including Data Science, Engineering, Product, and Business stakeholders, to understand complex business challenges and identify opportunities where AI can deliver measurable impact. You will lead the end-to-end lifecycle of AI initiatives - from problem framing and data exploration to model development, deployment, and monitoring - ensuring solutions are scalable, ethical, and aligned with enterprise … goals. Skills we would love you to have: Extensive experience in AI/ML engineering, data science, or applied machine learning roles. Proven track record of delivering production-grade AI solutions in complex, data-rich environments. Proficiency in Python and key ML libraries (e.g. Semantic Kernel, Langchain and Agentic frameworks). Experience deploying models into production using APIs, containers More ❯

ethical deployment of AI technologies, ensuring strict adherence to data privacy standards and regulations. What we are looking for: A university degree in Computer Science, Data Science, Artificial Intelligence, Engineering, or a related field. Proven experience in designing, developing, and deploying machine learning models and AI algorithms. Strong proficiency in programming languages such as Python, R, or Java. Solid … understanding of data processing, feature engineering, and data analytics. Ability to collaborate effectively with cross-functional teams including data scientists, engineers, and product managers. Strong problem-solving skills with attention to detail and the ability to handle complex datasets. Knowledge of data privacy standards, ethical AI practices, and regulatory compliance. Why you will love working with us Competitive More ❯

DBT, Delta Live Tables, and dimensional modelling to deliver consistent, trusted analytics. Enable advanced AI and ML use cases by building pipelines for vector search, retrieval-augmented generation (RAG), feature engineering, and model deployment. Ensure security and governance through robust access controls, including RBAC, SSO, token policies, and pseudonymisation frameworks. Develop resilient data flows for both batch and … pseudonymisation and retention policies Exposure to enabling GenAI and ML workloads by preparing model-ready and vector-optimised datasets Demonstrated capability to collaborate successfully with interested parties in data engineering, analytics, architecture, and business teams Advanced SQL skills and a keen focus on performance tuning, data integrity, and reusable compose patterns across data products Additional Information What’s in More ❯