26 to 50 of 140 Feature Engineering Jobs in London

statistical arbitrage strategies. The position will collaborate closely with the Portfolio Manager and other team members, contributing across all stages — from data processing and feature engineering to backtesting and live deployment. Key ResponsibilitiesResearch, design, and implement predictive signals and features across global equities. Work with large, diverse datasets … develop robust feature engineering and point in time (PIT) data cleaning pipelines. Collaborate with team members to implement research infrastructure, backtesting frameworks, and analytical tools. Build frameworks and tools for performance attribution and ongoing live strategy monitoring. Requirements2–8 years of experience in quant equities, with a primary ...

emerging AI technologies and recommend practical applications across the organisation.### Data Science & Analytics* Perform advanced statistical analysis and modelling across large-scale operational and engineering datasets.* Develop feature engineering, experimentation and model evaluation frameworks.* Create insights and recommendations that drive decision making for senior stakeholders.* Build … maintain reproducible data science workflows and pipelines.### Product Delivery* Partner with engineering and product teams to transition solutions from proof-of-concept into production.* Define success metrics and measurement frameworks for AI products.* Support model monitoring, governance and continuous improvement activities.* Contribute to AI product roadmaps and prioritisation discussions.### ...

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 ResponsibilitiesTechnical Leadership & ArchitectureDefine the end‐to‐end ML architecture for the matching platform, including data pipelines, model training workflows, inference ...

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 ...

Solirius Reply, part of the Reply Group, is a technology consultancy and digital transformation partner that helps organisations solve complex challenges through strategy, design, engineering, and delivery. We work closely with our clients to deliver secure, accessible, user-focused services that evolve with their needs. By combining deep technical … Ministry of Housing, Communities and Local Government, UEFA, International Olympic Committee, and Mercedes-Benz. Our services span the full digital delivery lifecycle, including architecture, engineering, delivery management, user-centred design, business analysis, data, DevOps, and AI.We operate as a collaborative and inclusive organisation that empowers our people to take ...

Solirius Reply, part of the Reply Group, is a technology consultancy and digital transformation partner that helps organisations solve complex challenges through strategy, design, engineering, and delivery. We work closely with our clients to deliver secure, accessible, user-focused services that evolve with their needs. By combining deep technical … Ministry of Housing, Communities and Local Government, UEFA, International Olympic Committee, and Mercedes-Benz. Our services span the full digital delivery lifecycle, including architecture, engineering, delivery management, user-centred design, business analysis, data, DevOps, and AI. We operate as a collaborative and inclusive organisation that empowers our people ...

Engineer to design, build and operationalise advanced machine learning solutions that directly support UK national security objectives. This role sits within a multidisciplinary AI engineering environment, working closely with Data Scientists, Software Engineers, Product teams and government stakeholders. The Senior ML Engineer will own the journey from experimentation … including hypothesis definition, experimental design, evaluation and iteration, while complying with governance standards Transitioning validated experiments into production-ready ML services, collaborating closely with engineering teams on deployment and monitoring Building scalable ML pipelines using AWS services and modern experiment tracking frameworks Developing and integrating LLM-powered capabilities ...

seeking an AI Data Scientist to help build intelligent, data-driven products. You will design, develop, and deploy machine learning models, working across data engineering and analytics to solve complex business problems. Youll collaborate with product, engineering, and business teams to transform data into actionable insights and high … models (e.g., predictive models, NLP, computer vision, recommender systems). Explore, cleanse, and transform large structured and unstructured datasets Conduct statistical analysis, experiment design, feature engineering, and model evaluation. Build scalable data pipelines and automate model training and inference processes. Collaborate with engineering teams to integrate models ...

seeking an AI Data Scientist to help build intelligent, data-driven products. You will design, develop, and deploy machine learning models, working across data engineering and analytics to solve complex business problems. You'll collaborate with product, engineering, and business teams to transform data into actionable insights … models (e.g., predictive models, NLP, computer vision, recommender systems). Explore, cleanse, and transform large structured and unstructured datasets Conduct statistical analysis, experiment design, feature engineering, and model evaluation. Build scalable data pipelines and automate model training and inference processes. Collaborate with engineering teams to integrate models ...

experienced Databricks architects who combine deep technical expertise with strategic thinking and delivery leadership. You'll work alongside exceptional data, AI, cloud, and engineering specialists to define enterprise architectures that enable organisations to modernise their data estates and accelerate AI adoption. We are seeking an experienced Databricks Architect … will: Lead the architecture and technical strategy for large-scale Databricks Data & AI transformation programmes. Define end-to-end solution architectures spanning data engineering, analytics, machine learning, and Generative AI workloads. Establish enterprise data architectures, medallion design patterns, data models, semantic layers, and governance frameworks using capabilities such ...

value-based decisioning logic — incorporating CLV and long-term customer value into prioritisation, not just short-term conversion Measurement frameworks and optimisation Define feature engineering requirements — knowing which signals, triggers, and contextual features drive predictive power in decisioning Architect real-time decisioning solutions integrating with … SNGCR01 Required — Technical Skills Advanced Python — writing clean, production-grade code, not just scripts (OOP, async, packaging, testing) Generative AI & LLM development — prompt engineering, fine-tuning, RAG pipelines, context window management Agentic AI frameworks — LangChain, LangGraph, AutoGen, or similar; building multi-step autonomous workflows Machine Learning — model development, training ...

value-based decisioning logic — incorporating CLV and long-term customer value into prioritisation, not just short-term conversion Measurement frameworks and optimisation Define feature engineering requirements — knowing which signals, triggers, and contextual features drive predictive power in decisioning Architect real-time decisioning solutions integrating with … SNGCR01 Required — Technical Skills Advanced Python — writing clean, production-grade code, not just scripts (OOP, async, packaging, testing) Generative AI & LLM development — prompt engineering, fine-tuning, RAG pipelines, context window management Agentic AI frameworks — LangChain, LangGraph, AutoGen, or similar; building multi-step autonomous workflows Machine Learning — model development, training ...

data solutions and AI-assisted capabilities on modern cloud platforms. You'll build scalable data pipelines, optimize data quality and governance and enable ML feature engineering for analytics and intelligent applications. The role requires hands-on technical expertise in data engineering and AI integration while driving reliability … optimized for AI/ML pipelines and advanced analyticsDevelop streaming and batch pipelines leveraging tools like Azure Data Factory and DatabricksOperationalize ML solutions, integrating feature stores, model registries and inference endpointsCollaborate with data scientists to deploy and monitor AI models using enterprise MLOps frameworksIntegrate GenAI-assisted development methods into ...

live decisioning frameworksUse value-based decisioning logic — incorporating CLV and long-term customer value into prioritisation, not just short-term conversionMeasurement frameworks and optimisationDefine feature engineering requirements — knowing which signals, triggers, and contextual features drive predictive power in decisioningArchitect real-time decisioning solutions integrating with … offerings#LI-EU SNGCR01 Required — Technical SkillsAdvanced Python — writing clean, production-grade code, not just scripts (OOP, async, packaging, testing)Generative AI & LLM development — prompt engineering, fine-tuning, RAG pipelines, context window managementAgentic AI frameworks — LangChain, LangGraph, AutoGen, or similar; building multi-step autonomous workflowsMachine Learning — model development, training, evaluation ...

experienced Databricks architects who combine deep technical expertise with strategic thinking and delivery leadership. You'll work alongside exceptional data, AI, cloud, and engineering specialists to define enterprise architectures that enable organisations to modernise their data estates and accelerate AI adoption. We are seeking an experienced Databricks Architect … delivery planning, resourcing, dependency management, financial oversight, commercial management, risk and issue management, and stakeholder reporting. Define end-to-end solution architectures spanning data engineering, analytics, machine learning, and Generative AI workloads. Establish enterprise data architectures, medallion design patterns, data models, semantic layers, and governance frameworks using capabilities such ...

experience in financial services (banking, capital markets, insurance, or fintech) to design, build, and scale GenAI-powered data solutions. The role combines modern data engineering, ML/LLM integration, and domain-specific financial knowledge to deliver enterprise-grade AI platforms. You will lead the development of data pipelines, vector … integration with enterprise applications.* Monitor, evaluate, and enhance model performance, scalability, reliability, and accuracy in production environments.* Collaborate with business stakeholders, data scientists, and engineering teams to translate requirements into effective AI solutions.* Contribute to prompt engineering, AI workflow development, and end-to-end solution implementation.* Support deployment ...

Analysis: Develop, train and evaluate models using statistical and machine learning techniques, with a focus on probabilistic approaches. Contribute across the modelling lifecycle from feature engineering and training through to validation and deployment. Data Work: Query, clean and explore datasets using Python and SQL to surface patterns … statistical techniques. Comfortable working with probabilistic models, uncertainty estimation and Bayesian inference. Model Development: Understanding of the full model training pipeline, including data preparation, feature selection, model selection and model validation. Experience: Hands-on experience building and evaluating models in a data science or quantitative context. Python & SQL: Comfortable ...

will work at the intersection of Computer Science, Mathematics, and Statistics — building high-performance tools that enable world-class research while maintaining a high engineering standard. Responsibilities Partner with PhD researchers to design, implement, and productize machine learning models that drive quantitative trading strategies Develop and maintain complex data … pipelines, including data ingestion, feature engineering, validation, and quality monitoring Translate research prototypes and novel ideas into performant, well-tested, production-ready code Build extensible tools and frameworks that accelerate the model development and experimentation lifecycle Supervise, understand, and remediate subtle data quality issues across both research ...

products. These capabilities will support R&D products, AI applications, client intelligence and firm-wide decision support. This is a hands-on hybrid data-engineering and applied-data-science role, with particular responsibility for building data products in Microsoft Fabric and Databricks. You will work with Data Programme colleagues … data assets using agreed patterns, without duplicating enterprise platform responsibilities. You will join a small, hands-on multidisciplinary team working collaboratively across discovery, prototyping, engineering, productionisation and continuous improvement. Key Responsibilities Partner with the Data Programme, data owners and system teams to assess, access and combine priority internal ...

with high autonomy, owning your projects from the initial exploratory analysis through to production deployment. In this role, you will work closely with Product, Engineering, and Business stakeholders to deliver solutions that optimize our operations, refine our marketing efforts, and enhance the customer experience. You will not only build … powerful models but also help uphold the engineering rigor and standards of our data team. You Will: Build from Scratch: Thrive in a 0-to-1 environment. You are comfortable rolling up your sleeves to write complex SQL, engineer your own features, and deploy baseline models (heuristics or simple ...

roadmaps, align on requirements, and deliver data‐led transformations Establish reusable, modular data science and machine learning capabilities that scale across use cases, including feature engineering, evaluation harnesses, prompt tooling patterns, agent frameworks, orchestration, and context and memory management Provide technical leadership and mentorship through code reviews, design … reviews, best practices, and upskilling across data science and engineering partners Communicate with technical and non‐technical stakeholders, translating model outputs into decisions, tradeoffs, and operational plans Maintain strong documentation for approaches, model cards, runbooks, and operational procedures Required Qualifications, Capabilities, and Skills Master’s degree in a quantitative ...

roadmaps, align on requirements, and deliver data-led transformations Establish reusable, modular data science and machine learning capabilities that scale across use cases, including feature engineering, evaluation harnesses, prompt tooling patterns, agent frameworks, orchestration, and context and memory management Provide technical leadership and mentorship through code reviews, design … reviews, best practices, and upskilling across data science and engineering partners Communicate with technical and non-technical stakeholders, translating model outputs into decisions, tradeoffs, and operational plans Maintain strong documentation for approaches, model cards, runbooks, and operational procedures Required Qualifications, Capabilities, and Skills Master's degree in a quantitative ...

level of experience and qualifications by reading the full overview of this opportunity below. You’ll be central to delivering a robust, high-performing engineering foundation that powers analytics, operational data flows, and future AI capabilities across our global events and digital products. This role is primarily focused … engineering excellence, developing high-quality pipelines, modelling data in line with our Medallion Architecture, and ensuring our Databricks platform is secure, governed, and production ready. Key Responsibilities Design, build, and optimise scalable data pipelines using Databricks, Delta Live Tables, Synapse, and Delta Lake. Develop ingestion, transformation, and orchestration workflows ...

distributed computing (e.g., Spark, Dask) and ensure robust test coverage for production systems. Mentor junior team members and utilise model explainability methods to drive feature performance improvements. About You 5+ years of experience in designing, building and maintaining machine learning models to solve complex, large-scale business problems. Deep … statistics, plus supervised and unsupervised modelling techniques. Proven experience modelling complex interactions (e.g., cluster or network effects). Expertise in model explainability to tune feature engineering and understand feature interactions. Ability to write high-quality, production-grade Python code and collaborate effectively with non-technical stakeholders. Proficient ...

Azure and Databricks to help build, optimise, and scale Clarion’s modern data platform. You’ll be central to delivering a robust, high-performing engineering foundation that powers analytics, operational data flows, and future AI capabilities across our global events and digital products. This role is primarily focused … engineering excellence, developing high-quality pipelines, modelling data in line with our Medallion Architecture, and ensuring our Databricks platform is secure, governed, and production ready. Key Responsibilities: Design, build, and optimise scalable data pipelines using Databricks, Delta Live Tables, Synapse, and Delta Lake. Develop ingestion, transformation, and orchestration workflows ...