19 of 19 Feature Engineering Jobs in London

hire has very meaningful impact.They are looking for a Senior Data Scientist to lead the predictive analytics capability and their critical programme.You’ll design feature engineering pipelines, select and validate classification and regression models, and establish rigorous evaluation methodology (targeting AUC-ROC 0.85) across a 300M+ point education … explainable and production-ready.Core Responsibilities: Predictive Model Development : Build and validate supervised learning models (classification & regression) using complex, multi-source, time-series-influenced data. Feature Engineering : Design scalable feature pipelines across attendance, behaviour, wellbeing, assessment and SEND datasets. Evaluation & Methodology : Establish rigorous evaluation frameworks including ...

building, and deploying scalable machine learning solutions to enable advanced analytics, automation, and decision-making across complex government systems. This is a hands-on engineering role, working closely with data scientists, analysts, architects, and product teams to productionise models, build data pipelines, and embed ML capabilities into live services. … Synapse) Experience in AWS environments is beneficial Experience with MLOps practices and tools (CI/CD pipelines, model monitoring, versioning) Strong understanding of data engineering concepts (ETL pipelines, data lakes, feature engineering) Experience working with large-scale structured and unstructured datasets Knowledge of AI ethics, bias mitigation ...

business priorities Translate use cases into scalable, production-ready architectures Provide C-suite advisory on AI adoption, governance, and operating models Enterprise AI Platform Engineering Design and implement cloud-native MLOps platforms across AWS, Azure, and GCP Enable end-to-end ML lifecycle : data → training → deployment → monitoring Build secure … Ensure responsible AI, explainability, and governance by design Data & Real-Time Intelligence Implement real-time and batch data pipelines (Kafka, Spark, Airflow) Enable advanced feature engineering and predictive analytics Support streaming inference and operational AI use cases Scaled Delivery & Transformation Lead multi-disciplinary AI teams across engineering ...

model selection, and architecture decisions Conduct exploratory data analysis and communicate insights Collaborate with data engineers, architects, and business analysts on integrated solutions Build feature‐engineering pipelines and automated data preparation workflows Design AI solutions for commercial transformation including pricing optimization, customer segmentation, and revenue management Develop scalable … proposals and technical assessments for new opportunities and internal knowledge transfer Essential Qualifications Degree or equivalent certification in Computer Science, Data Science, Statistics, Mathematics, Engineering, or related quantitative field Proven experience building and implementing LLM‐based solutions (GPT, Claude, Llama, Mistral, or similar) Hands‐on experience with at least ...

/ML features, from data ingestion and training to deployment, MLOps workflows, CI/CD, and model versioning Develop LLM/GenAI solutions: prompt engineering, RAG pipelines, embeddings, vector search, and inference optimisation (LoRA/PEFT, quantisation, GPU/TPU) Own observability across data, models, and prompts … Responsible AI practices throughout What you'll need Hands-on LLM/GenAI experience (Gemini or open source) including fine-tuning, RAG pipelines, prompt engineering, and graph-based workflows (ADK, MCP) Strong Python, API/microservices development, GCP (Vertex AI, BigQuery), CI/CD, and containerisation (Docker, Kubernetes) Nice ...

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 ...

governance frameworks to ensure responsible AI/ML model deployment. Use Python to automate processes and optimise workflows. Handle large datasets, including data preprocessing, feature engineering, and model evaluation. Lead the agile development of AI solutions from concept through deployment and ongoing improvement. Create and maintain comprehensive technical … documentation. Communicate complex AI concepts clearly to stakeholders at all levels. What you'll bring: Proven experience (3 years) in AI solution engineering, with a focus on large language models, prompt engineering, and RAG implementations. Strong skills in data analytics, MLOps practices, and API development. Knowledge of governance ...

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 ...

Collaborate with data engineers, analysts, and product teams to translate business needs into AI-driven solutions Contribute to the development of data pipelines and feature engineering workflows Integrate models into production using APIs, batch jobs, or real-time systems Apply best practices around experimentation, evaluation, versioning, and monitoring ...

Bring Hands‐on experience in data science or applied machine learning. Strong understanding of Generative AI, LLMs, and RAG principles. Experience with data mapping, feature engineering, and end‐to‐end ML lifecycle management. Proficiency across Microsoft's Azure AI and data ecosystem, with an eagerness to adopt Fabric ...

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 ...

Solid Python programming skills and understanding of machine learning fundamentals. Growing familiarity with AI technologies, particularly LLMs and Azure OpenAI. Experience with data preparation, feature engineering, and model evaluation. Good communication skills and ability to explain technical concepts to non-technical audiences. A commitment to Movar's IDEAL ...

topics, including: Fundamentals of ML and AI (including Machine Learning Lifecycle, Machine Learning Mathematical Foundations); Solving Business Problems with Machine Learning; Data Preparation and Feature Engineering; Planning and preparing ML/AI solution; Data Ethics and Responsible AI; Model Engineering and Training; Model Evaluation and Deployment; Monitoring ...

Function focused on embedding AI into the core of how products are designed, engineered, delivered, and supported. This is not a traditional 'AI feature engineering' role. You'll help shape AI-native ways of working across the business - designing agentic workflows, integrations, and orchestration layers that connect teams … systems, and stages of the product lifecycle. The focus is on building intelligent systems that reduce friction, surface context, automate workflows, and improve how engineering, QA, delivery, sales, and product teams operate together. What you'll be doing: Designing and building agentic AI workflows across multiple business functions Building ...

model Data Preprocessing: Design, build, and maintain robust ETL/ELT pipelines to ingest, transform, and load data from various sources. AI model Feature Engineering: Integrate structured and unstructured data from internal and external systems into centralized data platforms. Performance Tuning of AI/models: Optimize data workflows ...

architectures. AI model Data Preprocessing: Design, build, and maintain robust ETL/ELT pipelines to ingest, transform, and loaddata from various sources. AI model Feature Engineering: Integrate structured and unstructured data from internal and external systems intocentralized data platforms. Performance Tuning of AI/models: Optimize data workflows ...

experimentation strategy for the product area — designing A/B tests and multi-armed bandit experiments that generate genuine learning about AI feature performance, not just validate existing assumptions Drive the feedback loop strategy — defining how member behaviour is captured, modelled, and fed back into AI ranking systems … context, using results to change direction rather than confirm instinct Technically credible AI and ML fluency — able to read a model card, challenge a feature engineering decision, write testable acceptance criteria for ML features, and explain confidence intervals to non-technical stakeholders, without overstepping into engineering decisions ...

into data, surface anomalies, communicate findings frequently, and drive actions across teams. Good to have FinTech/payments and Fraud experience. Experience with feature engineering and model monitoring. Familiarity with Airflow/DBT/Git/Snowflake and production data platforms. If you care about protecting customers ...

Function focused on embedding AI into the core of how products are designed, engineered, delivered, and supported. This is not a traditional 'AI feature engineering' role click apply for full job details ...