1 to 25 of 32 Remote/Hybrid Feature Engineering Jobs in England

Machine Learning, Artificial Intelligence, Predictive Analytics, Statistical Modelling, Python, SQL, PySpark, Azure, Databricks, MLflow, GitHub Actions, CI/CD, Time Series Forecasting, Propensity Modelling, Feature Engineering, Data Engineering, Azure Machine Learning, Azure Data Platform, Experiment Design, A/B Testing, Hypothesis Testing, Predictive Modelling, Customer Analytics, Marketing … that improve customer outcomes, enhance commercial performance & support strategic business decision making. Own the complete analytical lifecycle, from initial problem definition & exploratory analysis through feature engineering, model development, deployment, operational monitoring & continuous optimisation. Build sophisticated statistical & machine learning models covering areas such as: * Customer Lifetime Value * Customer Propensity ...

natural language processing [NLP]/and neural networks [NN]) you will be part of a small, central function that partners closely with product and engineering teams on a single, shared roadmap, with a one‐team mentality throughout. We take a test‐and‐learn approach: real experiments, time‐boxed … data with external reference sources to support faster, better decisions. Deployment & monitoring. Deploying and monitoring machine learning (ML) models in production, with the engineering discipline to catch drift and issues early. Cross‐team support. Occasional collaboration on NLP/NN‐related work led by our existing senior data scientist ...

Experience designing and analysing A/B tests, defining success metrics, understanding selection bias, and evaluating ranking systems using both online and offline methodologies. Feature Engineering & Applied Machine Learning : Strong background in feature engineering, tabular machine learning, calibrated scoring systems, and production use of models such … Entity‐Aware Ranking : Ability to incorporate relationships between companies, sponsors, lenders, law firms, instruments, documents, and events into ranking and recommendation decisions. Production ML Engineering : Experience building feature pipelines, online and batch inference systems, low‐latency ranking services, experimentation platforms, and monitoring for production machine learning systems. Strong ...

Principal, AI/ML Engineer leads the design, delivery and continuous improvement of AI and ML solutions within their area of responsibility, aligning engineering activities to the Bank’s broader AI strategy and long-term objectives. The role combines strong technical leadership with a clear focus on delivery outcomes … operates with a clear understanding of the wider technology landscape, contributing to strategic direction while taking accountability for translating this into practical, high-quality engineering outcomes across squads. Leads the definition and execution of AI/ML engineering direction across one or more squads, ensuring alignment with ...

science and find new ways to connect and protect our world. Raytheon brings the strength of more than 100 years of experience and renowned engineering expertise to meet the needs of today's mission and stay ahead of tomorrow's threat. We deliver solutions that help our nation …/ML solutions aligned to Army training objectives and enterprise architecture principles. Support the development and maintenance of ML pipelines including data preprocessing, feature engineering, model training, validation, and performance evaluation. Support integration of AI capabilities into secure operational environments, ensuring compatibility with DevSecOps pipelines and platform constraints. ...

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 ...

systems behind ad relevance, bid and yield optimization, and real-time, low-latency ad serving. This is a senior, hands-on ML engineering role spanning modelling, large-scale training, and production infrastructure — you’ll take models from idea through to serving at scale, working in Spark, Python, and Java. … automation to move faster, raise the bar, and scale their impact.We value your AI skills if you have built fluency across the agentic engineering toolchain — coding harnesses like Claude Code or Cursor, MCP servers, custom skills, or agent frameworks — and can describe projects where you shipped real work with ...

well-positioned to help shape the future of streaming. Continued success relies on building customer relationships with Roku that delight and engage them.Within Advertising Engineering, the MarTech team builds the products, services, and machine learning systems that help Roku deliver the right communication, creative, and marketing experience … pair a global mindset with locally relevant execution. You should be a gritty problem solver and self-starter who can work effectively with engineering, product, data science, and commercial stakeholders across Roku. The successful candidate will display a balance of hard and soft skills, including the ability to respond ...

positioned to help shape the future of streaming. Continued success relies on building customer relationships with Roku that delight and engage them. Within Advertising Engineering, the MarTech team builds the products, services, and machine learning systems that help Roku deliver the right communication, creative, and marketing experience … pair a global mindset with locally relevant execution. You should be a gritty problem solver and self-starter who can work effectively with engineering, product, data science, and commercial stakeholders across Roku. The successful candidate will display a balance of hard and soft skills, including the ability to respond ...

world.As a Principal Data Engineer you will set the medium to long term technical direction for our data infrastructure. You will partner with Engineering, Data Science, Product and SRE leadership on cross-tribe initiatives, coach engineers at every level, and tackle the data problems that no single team … solve alone. You will also represent ComplyAdvantage at engineering and industry events.Your impact will shape the data foundations on which ComplyAdvantage's AI, screening and monitoring products are built. Your work will directly affect how quickly and accurately our customers can detect money laundering, terrorist financing, sanctions evasion ...

bridge the gap between machine learning, data science, and engineering. What you’ll do Shape the architecture of data products built for: analytics forecasting feature engineering customer behavior insights integration of new data sources Data Transformation & Governance Lead best practices in: data modelling performance optimization governance consistent reliable … Explore open-source tools Engage with the broader tech community Help keep Prima at the cutting edge What we’re looking for Software & Data Engineering Strong expertise in Python Passion for writing: clean reliable production-grade code Distributed Data Processing Experience building and operating: batch processing systems distributed data ...

with new estimators, models and features to boost payment performance across our portfolio of merchants. You will work closely with Data Scientists, Product and Engineering to enhance our core offering, protect customer lifetime value through network intelligence, and ensure safe model launches through robust observability.Key ResponsibilitiesContribute to the research … with other Data Scientists and engineers to productionise ML features, models and evolve our evaluation and monitoring frameworks.Write high-quality, interpretable Python code for feature engineering and model training, contributing directly to our core products.Communicate hypotheses, evaluation results, and monitoring dashboards clearly to both technical and non-technical ...

experimenting with new estimators, models, and features to boost payment performance across our merchants portfolio. You will work closely with Data Scientists, Product, and Engineering to enhance our core offering, protect customer lifetime value through network intelligence, and ensure safe model launches through robust observability. Key Responsibilities Contribute … other Data Scientists and engineers to productionise ML features, models, and evolve our evaluation and monitoring frameworks. Write high‐quality, interpretable Python code for feature engineering and model training, contributing directly to our core products. Communicate hypotheses, evaluation results, and monitoring dashboards clearly to both technical ...

positioned to help shape the future of streaming. Continued success relies on building customer relationships with Roku that delight and engage them. Within Advertising Engineering, the MarTech team builds the products, services, and machine learning systems that help Roku deliver the right communication, creative, and marketing experience … using code for statistical analysis and tool building, using both general‐purpose software and statistical languages. What You’ll Be Doing Data Analysis/Feature Engineering: Apply your expertise to identify and calculate features that can be leveraged by multiple use cases as well as models. Train Machine ...

before production deployment. Develop robust ML pipelines using AWS services and MLOps tooling. Implement experiment tracking, model versioning, monitoring, and reproducibility best practices. Build feature engineering pipelines and contribute to feature store development. Monitor production models, optimise performance, and drive continuous improvements. Apply Responsible AI principles, including … technical concepts to both technical and non-technical stakeholders. Desirable Experience AI agents and agentic workflows. Vector databases such as Pinecone, Weaviate, or pgvector. Feature stores including Feast or AWS Feature Store. Docker, Kubernetes, or Amazon ECS. Infrastructure as Code using Terraform or CloudFormation. Big data processing technologies ...

Experience designing and analysing A/B tests, defining success metrics, understanding selection bias, and evaluating ranking systems using both online and offline methodologies.Feature Engineering & Applied Machine Learning: Strong background in feature engineering, tabular machine learning, calibrated scoring systems, and production use of models such as gradient … environments.Graph & Entity-Aware Ranking: Ability to incorporate relationships between companies, sponsors, lenders, law firms, instruments, documents, and events into ranking and recommendation decisions.Production ML Engineering: Experience building feature pipelines, online and batch inference systems, low-latency ranking services, experimentation platforms, and monitoring for production machine learning systems.Strong proficiency ...

product teams, AI agents, and external customers depend on for clean, reliable data.This Senior Manager role spans both teams. It is a data and engineering leadership role with a strong product backbone, designed for a builder-leader. You need to understand what good AI feature engineering looks … like, what it takes to build end-to-end data products, data engineering best practice, and how to build and lead teams that do both well. You will stay close enough to the work to shape technical direction, unblock delivery, and raise the quality bar across both teams.Who ...

using 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 You5+ years of experience in designing, building and maintaining machine learning models to solve complex, large-scale business problems.Deep understanding of frequentist … Bayesian 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 in leveraging LLMs ...

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 ...

value creation initiatives to be backed by reliable, real-time data. When companies partner with JMAN, we combine our data science and data engineering expertise with our deep commercial understanding to deliver tangible, high-value outcomes at pace. Founded in 2010, JMAN has a global footprint with offices … Data Science or applied machine learning, ideally in consulting, high‐growth, or commercial environments. Strong applied machine learning expertise, including: Model selection and development Feature engineering Evaluation and validation Deployment into production environments Demonstrated experience taking models beyond experimentation into operational, business‐critical systems. Strong background in statistics ...

professional services clients. Suits an experienced AI or software engineer with advanced Python, agentic frameworks and MLOps skills. Attercop is a knowledge engineering and agentic AI company built specifically for private equity and professional services. We turn fragmented, hard to use information into structured intelligence and deploy autonomous … transformation. Role Overview You’ll design, build, and integrate advanced AI models into real software systems. This role sits at the intersection of software engineering, data science, and MLOps — turning research into robust, scalable, production-ready AI services. Core Responsibilities Build functional AI services from architectural designs Orchestrate data ...

platform design. Ensure architectures meet security, privacy, and regulatory requirements, including GDPR and data residency considerations. Review solution designs, provide architectural assurance, and support engineering teams through design authority and peer review. Design data architectures that enable AI adoption — ensuring data is discoverable, well-governed, and AI-ready … machine learning, GenAI, and agentic use cases across the business. Partner with AI/ML teams to define patterns for feature engineering, model data pipelines, vector search, and safe exposure of enterprise data to AI systems. Evaluate emerging technologies and make pragmatic build/buy/adopt recommendations ...

learning models focused on user personalisation, including recommendation engines, ranking algorithms, user segmentation and content analysis. Construct and maintain robust, scalable data pipelines for feature engineering and model training, handling both structured and unstructured large‐scale datasets. Deploy and supervise ML models in production, ensuring high availability, optimal ...

Europe (Remote), Europe (Remote), United Kingdom Contract Location: Brighton (Hybrid)/Europe (Remote) About Attercop Attercop is a knowledge engineering and agentic AI company built specifically for private equity and professional services. We turn fragmented, hard to use information into structured intelligence and deploy autonomous AI agents that make … transformation. Role Overview You’ll design, build, and integrate advanced AI models into real software systems. This role sits at the intersection of software engineering, data science, and MLOps,turning research into robust, scalable, production-ready AI services. Core Responsibilities Build functional AI services from architectural designs Orchestrate data ...

rankers.Entity/relationship extraction/resolutionKnowledge Graphs; building and inference, graphRAGRecommendation systems and ranking: personalisation, learning-to-rank, feed ranking, user modelling, etc.Tabular ML: feature engineering, structured data modelling (GBDTs, etc.)Statistical & Predictive Modelling: supervised ML, anomaly detection, temporal modelling, etc.Deep understanding of the GenAI landscape and agentic ...