1 to 25 of 34 Remote/Hybrid Feature Engineering Jobs in London

workflows, and develop containerised model services that integrate directly into the OneView platform. This includes hands-on work with model architectures, feature engineering, model optimisation, performance debugging, schema-aligned data preparation, and ML-driven interfaces. This is a role for engineers who want to build real models, ship … real systems, and solve real operational ML problems - not just prototypes. You will work directly with production data, client technical teams, and our internal engineering ecosystem to deliver AI components that are robust, scalable, and deployed into live environments. Key Responsibilities Machine learning engineering Design, train and optimise ...

production environments. Key Responsibilities Design, develop, and optimise machine learning models for personalisation and recommendation use cases. Build and maintain scalable data pipelines for feature engineering, model training, and inference. Deploy, monitor, and improve ML models in production environments. Develop recommendation engines, ranking models, and user segmentation solutions. … Design and analyse A/B tests and offline experiments to measure model effectiveness. Work closely with Product, Engineering, Data, and Business teams to deliver impactful solutions. Research and evaluate emerging machine learning and deep learning techniques. Ensure models remain reliable, scalable, and aligned with business objectives. Required Skills ...

help millions more drivers in the UK and Spain. To help fuel that growth, we need a Senior Data Engineer to join our Engineering team. This team is the beating heart of Prima. You’ll be joining over 350 engineers across software development, infrastructure, operations, and security. Fueled … with a significant impact on the company’s growth. What you’ll do Shape the architecture of data products designed for: data analytics forecasting feature engineering customer behavior analysis integration of new data sources Data Transformation & Governance Lead best practices in: data modelling performance optimization data governance consistent ...

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 ...

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 … 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 ...

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 ...

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 ...

cannot be solved manually within reasonable timeframes (days/weeks). Develop problems requiring non-trivial reasoning chains in data processing, statistical analysis, feature engineering, predictive modeling, and insight extraction. Create deterministic problems with reproducible answers: avoid stochastic elements or require fixed random seeds for exact reproducibility. Base … practical applications. You are proficient in SQL and database operations for data manipulation and analysis. You have experience with GenAI technologies (LLMs, RAG, prompt engineering, vector databases). You have good understanding of MLOps practices and model deployment workflows. You possess knowledge of modern frameworks (TensorFlow, PyTorch, LangChain). ...

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 ...

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 rigour 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 ...

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 … 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 ...

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 ...

that turn real customer signals into timely actions and measurable outcomes allowing customers to amplify consumer voice for LLM visibility advantage. Partner across Product, Engineering, CS, and Commercial to make the human signal visible, actionable, and compounding in the product. Establish experimentation and measurement foundations: design how we test … into simple, trusted narratives that guide product and commercial decisions. Productionize and scale thoughtfully: ship durable data and model workflows in collaboration with the engineering team, ensure quality and monitoring, and document decisions so the system is reliable, explainable, and easy to evolve. What you’ll bring Track record ...

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 ...

decisions, improve customer outcomes, and build scalable data science capabilities for a growing product area. You will collaborate closely with cross-functional teams, including engineering, product, analytics, operations and risk management. Key Responsibilities: Lead the development and deployment of machine learning models and data science solutions to improve Receive … ensure state-of-the-art capabilities in the Spend domainA bit about you: Proven track record of deploying models from scratch, including data preprocessing, feature engineering, model selection, evaluation, and monitoringSolid knowledge of Python, and ability to make and justify design decisions in your code. You know ...

customers in more than 120 markets. ## **Role overview:** This is along-term **fixed-term contract** designed to support Planet’s AI-first engineering scale-up project. We're hiring a Data Scientist to join Planet's AI team and lead our commercial data science work. You'll partner … tests and quasi-experiments for commercial initiatives. Bring statistical rigour to business decisions.* **Productionisation** — Take models from notebook to production. Own the full lifecycle: feature engineering, training, deployment, monitoring, retraining.* **Stakeholder partnership** — Translate ambiguous commercial questions into well-scoped analytical problems. Communicate findings clearly to non-technical audiences. ...

Design and develop predictive, machine learning, and Generative AI solutions. Build prototypes, proof-of-concepts, and production-ready analytical models. Perform data exploration, feature engineering, model development, and validation. Collaborate with data engineers and architects to operationalise solutions. Ensure solutions follow Responsible AI, governance, and security best practices. ...

security, identity and compliance (Entra ID, RBAC, network isolation, data protection). Strong experience designing LLM‐based solutions, including Retrieval‐Augmented Generation (RAG), prompt engineering strategies and agent‐based architectures, leveraging frameworks such as Semantic Kernel, LangChain, and Microsoft Agent Framework. Deep practical experience with classical Machine Learning, including … supervised and unsupervised learning, feature engineering, model selection, training pipelines, evaluation frameworks and production lifecycle management, equivalent in depth to GenAI expertise. Proven ability to assess client use cases and make well‐reasoned architectural decisions between classical ML and Generative AI approaches; and articulate clearly why. Strong experience ...

financial services (ideally Anti-Financial Crime/Screening) Experience building Natural Language Processing (NLP)/Machine Learning (ML)/Artificial Intelligence (AI) pipelines, including feature engineering, model training, evaluation and monitoring Experience with hyperparameter tuning at scale and experimentation frameworks Strong technical experience with SQL and Python; significant ...

Experiment with supervised, unsupervised, semi-supervised, reinforcement, and deep learning techniques and algorithms Design and optimize machine learning pipelines and workflows, including data cleaning, feature engineering, model selection, and hyperparameter tuning Develop scalable and efficient machine learning infrastructure and systems for training, testing, and deploying models in production ...

algorithms, including supervised, unsupervised, semi-supervised, reinforcement, and deep learning; Design and optimize machine learning pipelines and workflows, incorporating techniques for data cleaning, feature engineering, model selection, and hyperparameter tuning; and Develop scalable and efficient machine learning infrastructure and systems for training, testing, and deploying models in production ...

/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 ...

Data Scientist to drive production‐ready ML solutions that impact business outcomes. You will translate complex data challenges into scalable models, spanning data extraction, feature engineering, experimentation, and deployment. You will work closely with Product, Engineering and Marketing to optimize campaigns, improve user experiences, and inform strategic … decisions, while maintaining engineering rigor and robust ML ops practices. #J-18808-Ljbffr ...