Data Science Jobs in London

• London
• Hybrid · 3 days in office
• Senior

Research engineers translate frontier research concepts into practical implementations, building and optimising state-of-the-art AI models such as Transformers, GNNs and diffusion models, plus the codebases, data pipelines and infrastructure for training and evaluation. The role spans the full ML lifecycle from experimentation and benchmarking to production integration, working closely with research scientists in a cross-disciplinary drug design team.

JAX · PyTorch · XLA +6

• London
• Hybrid · 3 days in office
• Mid-level · manages people

Conducts core machine learning research applying large language models to drug discovery, developing and refining LLM-driven approaches across biology and chemistry use cases. Builds and scales training and inference frameworks, tunes experiments, and collaborates with interdisciplinary scientists. Senior candidates may lead standalone projects and mentor the ML community.

JAX · PyTorch · TensorFlow +3

• London
• Senior

Serve as the trusted technical ML and AI expert for enterprise customers, architecting production-grade ML and AI workloads on the Databricks Data Intelligence Platform. Specialise in GenAI solutions including RAG architectures, agentic systems, MLOps and LLMOps, while mentoring colleagues and supporting the technical sales cycle with MVPs and deep-dive sessions.

Databricks · AWS · Azure +7

• London
• Hybrid
• Senior

Hybrid technical and commercial role acting as post-sale technical lead across all Databricks products for strategic accounts. You own the technical account strategy and execution plan, driving use cases from win to production, coordinating Solutions Architects, Professional Services and support teams, and reporting on usage, adoption and customer health.

Databricks · Lakehouse · Unity Catalog +4

• London
• Hybrid
• Senior
• Permanent

Lead original technical research in AI safety, steering projects from initial question to peer-reviewed publication. Work spans interpretability, steering vectors, goal drift, machine unlearning and uncertainty calibration for transformer LLMs and agentic systems, with outputs informing frontier labs and government institutes. Involves building reproducible research code in PyTorch and Python and collaborating with red-teaming and evaluation teams.

PyTorch · Transformer · Metaview

• London
• Hybrid
• Lead · manages people
• Permanent

Sets technical direction for complex AI/ML projects, leading delivery of large-scale platforms in high-risk national security environments. Designs scalable ML systems, drives shared libraries and CI/CD infrastructure, and oversees model deployment, versioning and testing. Also manages and coaches engineers while defending architectural decisions to senior stakeholders.

Kubernetes · TensorFlow · PyTorch +1

• London
• Hybrid · 3 days in office
• £85,000 – £95,000 pa
• Senior

Senior analytics business partner role sitting between analytics teams and commercial leadership, translating business priorities into an insights roadmap and coordinating analytics, research and BI resources. Covers marketing effectiveness, attribution, experimentation, MMM, pricing and forecasting, with heavy emphasis on influencing senior stakeholders and measuring business impact.

• London
• Hybrid
• £45,000 – £50,000 pa
• Mid-level
• Permanent

This role involves working closely with various teams to transform data into actionable insights using Power BI. Responsibilities include designing and maintaining dashboards, delivering analysis, and championing self-serve analytics. The position offers a mix of strategic and hands-on tasks, contributing to a significant data transformation project.

• London
• £90,000 – £120,000 pa

This role involves analyzing complex sports datasets to develop and refine quantitative models that inform trading strategies. You'll apply statistical techniques and probability to identify patterns in sports data, working closely with analysts, developers, and traders. The position emphasizes model validation, performance assessment, and clear communication of findings in a fast-paced, data-driven environment.

• London
• Remote
• £28,000 – £38,000 pa
• Entry level

A traineeship covering AI fundamentals, generative AI and LLMs, prompt engineering, workflow and business process automation, AI agents, no-code platforms and API integrations. Participants build a portfolio through realistic projects such as chatbots, automated business processes and process analysis, with mentoring and career guidance. No prior AI or automation experience is required.

Generative AI · Large Language Models · AI Agents +3

• London
• On-site
• Senior
• Permanent

Senior individual contributor building the shared platform, tooling and infrastructure for an interdisciplinary chem-bio research team. Work spans LLM-based agent systems, evaluation frameworks, cloud and container infrastructure, and production Python, translating varied research needs into maintainable systems while mentoring engineers without line management.

AWS · Kubernetes · Slurm +2

• London
• £600 – £750 pd
• Mid-level
• Contract

Develops and deploys machine learning models and data pipelines that shape decision-making, customer service and business performance. Works closely with ML and software engineers on integration and coding standards, and engages stakeholders to translate complex business problems into data science solutions. Retail context with scope for personalisation, recommendation and experimentation work.

• London
• Hybrid
• Senior
• Permanent

Owns the end-to-end product lifecycle for enterprise AI services within the Snowflake Cortex team, from discovery and roadmap definition to launch and metrics analysis. Leads a cross-functional pod of engineers, data scientists and solution architects, translating bespoke customer deployments into scalable platform features while working closely with GTM and customer leadership.

Snowflake · Snowflake Cortex · Snowflake Data Cloud

• London
• Remote
• £60,000 – £70,000 pa
• Mid-level
• Permanent · Flexible

This role involves extending and improving a 22-agent agentic AI platform that connects fragmented school data and surfaces actionable insights. Responsibilities include building and refining agent sub-graphs, improving prompt engineering, and contributing to LLM benchmarking. The platform uses LangGraph, integrates multiple LLMs, and operates in a cloud-native environment.

• London
• Hybrid
• Mid-level
• Permanent

Works directly with customers to own Gen AI strategy and implementation, building end-to-end LLM workflows and taking them to production at large scale. Operates in small teams like a hands-on AI startup CTO, feeding field learnings back into the Palantir AIP product suite. Requires travel up to 25% to client sites.

Palantir AIP