1 to 25 of 33 Permanent Feature Engineering Jobs in London

Lead, Applied Scientist and Research Engineer positions—for upcoming roles across applied machine learning, generative AI, MLOps and model productionisation. These are hands-on engineering roles where you'll build, train, ship and operate the models that drive real product behaviour and real business outcomes. You'll work across … lifecycle—from problem framing and data preparation through to model development, evaluation, deployment, monitoring and iteration. The role suits someone who pairs solid software engineering foundations with genuine ML rigour and a healthy scepticism about what models can and can't be trusted to do. Key Responsibilities Partner with ...

Lead, Applied Scientist and Research Engineer positions—for upcoming roles across applied machine learning, generative AI, MLOps and model productionisation. These are hands-on engineering roles where you'll build, train, ship and operate the models that drive real product behaviour and real business outcomes. You'll work across … lifecycle—from problem framing and data preparation through to model development, evaluation, deployment, monitoring and iteration. The role suits someone who pairs solid software engineering foundations with genuine ML rigour and a healthy scepticism about what models can and can't be trusted to do. Key Responsibilities Partner with ...

graph databases and knowledge graphs, to generate deep insights into financial markets and enhance Marquee’s platform engagement. We collaborate closely with Sales, Trading, Engineering, Product, Design, and other areas of the Global Markets Division, and directly with clients. Our global team comprises experts in financial markets, product structuring …/PyTorch), Jupyter, Trino, SQL, and gain exposure to graph database technologies. RESPONSIBILITIES AND QUALIFICATIONS Responsibilities: Design, build, and maintain robust data pipelines for feature engineering and model training, ensuring data quality, scalability, and explainability. Develop, train, and deploy state‐of‐the‐art machine learning models, with ...

Python and SQL skills Experience developing and deploying machine learning models into production environments Excellent understanding of statistical modelling, experimentation, and model evaluation Strong feature engineering and exploratory data analysis capabilities Experience communicating technical findings and insights to non-technical stakeholders A degree qualification (BSc, MSc, PhD etc. … innovation The Senior Data Scientist role will involve: Developing and deploying machine learning models to solve real-world business challenges Performing exploratory data analysis, feature engineering, model development, and evaluation Building forecasting, classification, segmentation, and predictive modelling solutions Designing and executing statistical analyses and experiments to support strategic ...

taxonomies, citations, metadata, and content from every scientific discipline. Apply the right technique to each problem, using approaches such as classification, regression, clustering, ranking, feature engineering, deep learning, embeddings, LLMs, retrieval, and generative AI. Develop capabilities for semantic search, information retrieval, entity extraction, content classification, recommendation, ranking, summarization … inference, experimentation, monitoring, and continuous improvement. Support deployment, monitoring, model maintenance, drift detection, automated retraining, and ongoing optimization of data science systems. Collaborate with engineering, product, UX, analytics, research, and domain experts, and communicate technical concepts, model behavior, insights, trade-offs, and recommendations clearly to technical and non-technical ...

taxonomies, citations, metadata, and content from every scientific discipline. Apply the right technique to each problem, using approaches such as classification, regression, clustering, ranking, feature engineering, deep learning, embeddings, LLMs, retrieval, and generative AI. Develop capabilities for semantic search, information retrieval, entity extraction, content classification, recommendation, ranking, summarization … inference, experimentation, monitoring, and continuous improvement. Support deployment, monitoring, model maintenance, drift detection, automated retraining, and ongoing optimization of data science systems. Collaborate with engineering, product, UX, analytics, research, and domain experts, and communicate technical concepts, model behavior, insights, trade-offs, and recommendations clearly to technical and non-technical ...

generating, deploying and continuously improving bespoke machine learning models for every customer. You'll work with large-scale behavioural event data, applying machine learning, feature engineering and experimentation to improve prediction accuracy and drive measurable customer outcomes. Working alongside highly experienced founders and recognised experts in machine learning … business. Skills & Experience Strong commercial experience building machine learning models in Python Excellent understanding of predictive modelling, classification or propensity modelling Experience with feature engineering, model evaluation and experimentation Comfortable working across the full machine learning lifecycle Experience working with cloud platforms and modern ML tooling Curious ...

technical leadership across the full lifecycle of machine learning systems powering a new matching platform. This role is accountable for defining ML architecture, establishing engineering standards, driving MLOps maturity, and ensuring that our models are scalable, secure, explainable, and governed to enterprise‐grade standards. You will contribute … compliance framework. This is a highly hands‐on, highly technical, principal‐level role that combines architectural vision with deep practical expertise in ML engineering and AWS-native MLOps. Key Responsibilities Technical Leadership & Architecture Define the end‐to‐end ML architecture for the matching platform, including data pipelines, model training ...

Join our global Quantitative Trading & Research (QTR) team, where you’ll apply your expertise in Derivatives Modelling, Financial Engineering, Data Science, and Quantitative Development. As part of JP Morgan’s leading QTR Group, you’ll innovate with unique analytics and mathematical models, enhancing business practices through automation. We develop … 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 ...

logistic regression, gradient boosting, random forests, clustering, NLP Proficient in Python and/or R, with strong experience in data quality, model development and feature engineering Strong command of SQL and familiarity with data engineering environments such as Databricks or similar Skilled in data visualisation and storytelling ...

audit requirements. Experience with GDPR and AI governance frameworks. Key responsibilities Build and deploy predictive and credit risk models. Lead exploratory data analysis, feature engineering, model validation and monitoring. Develop forecasting, simulation and stress-testing models. Work with data engineering teams to create modelling-ready datasets using ...

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 ...

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 ...

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 ...

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. ...