26 to 50 of 70 Feature Engineering Jobs in the UK

Responsibilitie sPerform exploratory data analysis (EDA) to uncover trends, anomalies, and opportunitie sDevelop and validate machine learning models (regression, classification, clustering, etc. )Conduct feature engineering, hypothesis testing, and model evaluatio nTranslate business requirements into data science use cases and analytical solution sDeliver actionable insights to drive optimisation, efficiency ...

Responsibilitie sPerform exploratory data analysis (EDA) to uncover trends, anomalies, and opportunitie sDevelop and validate machine learning models (regression, classification, clustering, etc. )Conduct feature engineering, hypothesis testing, and model evaluatio nTranslate business requirements into data science use cases and analytical solution sDeliver actionable insights to drive optimisation, efficiency ...

Responsibilitie sPerform exploratory data analysis (EDA) to uncover trends, anomalies, and opportunitie sDevelop and validate machine learning models (regression, classification, clustering, etc. )Conduct feature engineering, hypothesis testing, and model evaluatio nTranslate business requirements into data science use cases and analytical solution sDeliver actionable insights to drive optimisation, efficiency ...

limitations, and model performance. Build and productionize analytics that advance intraday/EoD automation (services, APIs, pipelines) with clear SLOs/SLA, observability, reliability engineering practices, and tight integration into trading/risk platforms. Provide technical leadership and mentorship; conduct code/method reviews, establish research engineering best … resourcing via data‐driven analysis, scenario studies, and clear articulation of trade‐offs. Lead development of ML/AI solutions end‐to‐end (feature engineering, model training/validation, MLOps, monitoring and drift management) with rigorous controls, documented governance, and demonstrable business value. Uphold standards for documentation, reproducibility ...

This is a senior individual contributor role with strong influence through mentorship, collaboration, and technical leadership. You will work closely with partners across product, engineering, and the business to design and deliver data‐driven solutions.We welcome candidates from a range of backgrounds and experiences who are excited to apply … Development** Lead by example through hands-on coding and model development. Design, prototype, and validate innovative solutions for high-impact problems. Partner with engineering teams to deploy models into production environments.* **Domain Expertise** Leverage deep knowledge of aviation, travel, or related industries to inform modeling approaches and deliver customer ...

Senior Data Scientist to take a leading role across a portfolio of technically demanding projects. You’ll operate end-to-end - shaping problem definitions, engineering data pipelines, developing advanced models, and ensuring outputs are robust, explainable and deployable in real-world settings. This is a hands-on role … impact. Key Responsibilities Translating complex, ambiguous problem statements into clear, actionable data science solutions. Owning the full data science lifecycle, from data ingestion and feature engineering through to modelling, evaluation and deployment. Developing statistical, machine learning and deep learning models to support high-impact, real-world decision making. ...

business goals Effective communication and collaboration skills, with demonstrated experience working across cross-functional teams Bachelor’s degree or higher in Computer Science, Software Engineering, or a related field. As a Software Engineer specializing in AI systems, you will play a key role in designing and implementing production-grade … agents using techniques such as retrieval-augmented generation, prompt optimization, fine-tuning, and reinforcement learning Develop end-to-end pipelines for data ingestion, feature engineering, model inference (batch and real-time), and integration of AI-driven workflows into production systems Collaborate with data scientists and machine learning engineers ...

problem definition through to deployment in live environments.* Design, build, and deploy machine learning models within Pega-based decisioning platforms.* Lead model development across feature engineering, training, validation, and ongoing performance monitoring.* Work closely with application and logic developers to embed models into operational decision workflows.* Develop statistical ...

Development: Design, train, and optimise machine learning models focused on user personalisation, encompassing recommendation engines, ranking algorithms, user segmentation, and content analysis. Data Pipeline Engineering: Construct and maintain robust and scalable data pipelines for feature engineering and model training utilising both structured and unstructured large-scale datasets. … with a team retrospective. Global OTT Technology Our team develops and supports market-leading video streaming services, underpinned by state-of-the-art engineering principles. We do this at huge scale: for over 50 million customers globally, spanning NBCUniversal Peacock in the US and Sky, NOW and SkyShowtime across ...

shape advanced machine learning solutions that directly influence digital campaign performance. You will operate as the technical authority for data science, working closely with engineering to bring models into production and scale their real-world impact. The Company They are a London-based technology business specialising in advertising … optimising campaign performance. Since launching in recent years, they have grown into a collaborative team of around 50, combining expertise across data science, engineering and digital media. Their SaaS platform integrates with major advertising ecosystems, leveraging large-scale datasets to drive smarter decision-making for their clients. The Role ...

that reflect risk assessment outcomes and model performance. Qualifications A bit about you: Proven track record of deploying models from scratch, including data preprocessing, feature engineering, model selection, evaluation, and monitoring. Strong Python knowledge. Ability to read through code, especially Java. Demonstrable experience collaborating with engineering ...

focus on data and digital capability. You'll sit within a dedicated data function, working closely with a Senior Data Scientist and collaborating across engineering, product and business teams to build models that get used, not just presented. Responsibilities as a Data Scientist: Conduct exploratory data analysis to identify … trends, patterns and anomalies across large datasets Build, refine and deploy machine learning models to solve business problems Perform data cleaning, feature engineering and transformation to ensure data quality and model suitability Support integration of models into business processes and operational systems Monitor deployed model performance and recommend ...

focus on data and digital capability. You'll sit within a dedicated data function, working closely with a Senior Data Scientist and collaborating across engineering, product and business teams to build models that get used, not just presented. Responsibilities as a Data Scientist: Conduct exploratory data analysis to identify … trends, patterns and anomalies across large datasets Build, refine and deploy machine learning models to solve business problems Perform data cleaning, feature engineering and transformation to ensure data quality and model suitability Support integration of models into business processes and operational systems Monitor deployed model performance and recommend ...

focus on data and digital capability. You'll sit within a dedicated data function, working closely with a Senior Data Scientist and collaborating across engineering, product and business teams to build models that get used, not just presented. Responsibilities as a Data Scientist: Conduct exploratory data analysis to identify … trends, patterns and anomalies across large datasets Build, refine and deploy machine learning models to solve business problems Perform data cleaning, feature engineering and transformation to ensure data quality and model suitability Support integration of models into business processes and operational systems Monitor deployed model performance and recommend ...

focus on data and digital capability. You'll sit within a dedicated data function, working closely with a Senior Data Scientist and collaborating across engineering, product and business teams to build models that get used, not just presented. Responsibilities as a Data Scientist: Conduct exploratory data analysis to identify … trends, patterns and anomalies across large datasets Build, refine and deploy machine learning models to solve business problems Perform data cleaning, feature engineering and transformation to ensure data quality and model suitability Support integration of models into business processes and operational systems Monitor deployed model performance and recommend ...

teams to align architecture with business objectives. Provide technical leadership and governance across AI work streams and delivery teams Drive best practice in AI engineering, model management, and data science operations Evaluate and select appropriate AI frameworks, tools, and cloud services to meet enterprise requirements Support the integration … systems Skills and Experience Proven experience delivering AI solutions at enterprise scale in production environments Strong background in Generative AI — including LLMs, prompt engineering, and model fine-tuning Hands-on experience with Hugging Face (model hub, Transformers, Inference API) Experience with AWS AI services (SageMaker, Bedrock, Rekognition, Comprehend ...

business and regulatory challenges .Collaborate with data scientists, engineers, and business stakeholders to build and deploy production-grade machine learning models .Perform data analysis, feature engineering, model training, validation, and optimization .Conduct exploratory data analysis (EDA) to identify patterns, anomalies, and emerging risk indicators .Develop and maintain classification … s.Experience wit h time-series analys is to identify trends and assess risks over tim e.Expertise i n exploratory data analysis (ED A) and feature engineerin g.Strong problem-solving skills and the ability to communicate complex analytical findings to technical and non-technical stakeholder s. ...

business and regulatory challenges .Collaborate with data scientists, engineers, and business stakeholders to build and deploy production-grade machine learning models .Perform data analysis, feature engineering, model training, validation, and optimization .Conduct exploratory data analysis (EDA) to identify patterns, anomalies, and emerging risk indicators .Develop and maintain classification … s.Experience wit h time-series analys is to identify trends and assess risks over tim e.Expertise i n exploratory data analysis (ED A) and feature engineerin g.Strong problem-solving skills and the ability to communicate complex analytical findings to technical and non-technical stakeholder s. ...

business and regulatory challenges .Collaborate with data scientists, engineers, and business stakeholders to build and deploy production-grade machine learning models .Perform data analysis, feature engineering, model training, validation, and optimization .Conduct exploratory data analysis (EDA) to identify patterns, anomalies, and emerging risk indicators .Develop and maintain classification … s.Experience wit h time-series analys is to identify trends and assess risks over tim e.Expertise i n exploratory data analysis (ED A) and feature engineerin g.Strong problem-solving skills and the ability to communicate complex analytical findings to technical and non-technical stakeholder s. ...

business and regulatory challenges .Collaborate with data scientists, engineers, and business stakeholders to build and deploy production-grade machine learning models .Perform data analysis, feature engineering, model training, validation, and optimization .Conduct exploratory data analysis (EDA) to identify patterns, anomalies, and emerging risk indicators .Develop and maintain classification … s.Experience wit h time-series analys is to identify trends and assess risks over tim e.Expertise i n exploratory data analysis (ED A) and feature engineerin g.Strong problem-solving skills and the ability to communicate complex analytical findings to technical and non-technical stakeholder s. ...

using Python, TensorFlow, PyTorch Work on supervised, unsupervised, and reinforcement learning problems Clean and process large datasets to extract insights and train algorithms Perform feature engineering to improve model accuracy Design ML pipelines and automate model deployment Collaborate with software engineers to integrate models into applications Use MLOps ...

then scale into production Shape problem definitions with stakeholders in ambiguous environments Bring best practices from adjacent industries into a high-performance setting Data Engineering & Architecture Design/maintain pipelines integrating telemetry/timing, video/image, event operations, and digital/commercial engagement data Develop APIs/services … secure-by-design delivery with cyber teams What we're looking for Essentials 5-10 years' experience in data science/AI/ML engineering Strong Python Production ML deployment experience (end-to-end) Strong SQL + modern data warehouse experience Cloud familiarity + containerisation/orchestration Streaming data ...

advanced ranking models for Depop’s entire app, covering personalised recommendations, search results and other surfaces. Collaborate closely with cross-functional partners (product, engineering, data) to define problems, translate them into scalable solutions, and deliver measurable business outcomes. Lead the end-to-end lifecycle of ML projects: from ideation … data acquisition, feature engineering, training, and evaluation to deployment and ongoing iteration. Drive innovation in ranking by researching and integrating emerging ML techniques, frameworks, and tooling, while contributing technical expertise to long-term product and data strategy. Mentor, coach, and set technical direction within the Ranking ML team ...

expertise to make sense of complex data, working in close collaboration with our business partners. This role will primarily focus on feature engineering and insight generation from new types of data and the development of machine learning models to address critical business challenges in underwriting. We are interested … Develop and maintain the machine learning models which define our competitive advantage in the financial services market. Explore and evaluate data, using advanced feature generation and categorisation techniques, in order to stay at the forefront of innovation. Analyse tabular and non-tabular data, such as text, logs, or time ...

expertise to make sense of complex data, working in close collaboration with our business partners. This role will primarily focus on feature engineering and insight generation from new types of data and the development of machine learning models to address critical business challenges in underwriting. We are interested … Develop and maintain the machine learning models which define our competitive advantage in the financial services market. Explore and evaluate data, using advanced feature generation and categorisation techniques, in order to stay at the forefront of innovation. Analyse tabular and non-tabular data, such as text, logs, or time ...