Top Data Science Jobs in London

Leads a 25+ person organization of data scientists, machine learning engineers, and analytics engineers across Identity and Financial Crime. Owns data quality, governance, lineage, observability, fraud and financial-crime models, production performance, monitoring, retraining, and domain data products. Partners with engineering, product, risk, compliance, legal, and central data teams; influences upstream teams, develops managers and senior ICs, handles incidents, and scales hiring and technical strategy.

Designs and delivers enterprise AI solutions using Claude. Acts as a pre-sales technical advisor, translating customer needs into scalable architectures, guiding evaluations and deployments, presenting to technical and executive audiences, and coordinating with Sales, Product, and Engineering. The role requires customer-facing architecture experience, enterprise integration expertise, Python familiarity, LLM knowledge, German and English fluency, and occasional customer travel.

Principal Solution Engineer responsible for helping UK customers evaluate and adopt Snowflake. Partners with sales teams, channel partners, and customers to present solutions, conduct demos and proofs of concept, design architectures, develop technical champions, and secure technical wins. Requires strong modern data, cloud, SQL, presentation, and customer-facing skills. The role also involves competitive positioning, partner collaboration, account planning, and representing Snowflake at industry events.

Leads and develops a team of Data Scientists and other Data professionals, setting strategic direction and identifying high-impact opportunities. Partners with Product, Engineering, and senior stakeholders to shape product strategy and influence decisions through experimentation, causal inference, statistical modelling, machine learning, and analytics. Ensures analytical work drives measurable customer and commercial outcomes while collaborating with other data disciplines on tooling and infrastructure. Also contributes to hiring, coaching, technical standards, and the broader Data Science practice.

Lead a financial crime data science team focused on detecting, preventing, and mitigating financial crime. Partner with Product, Risk, Engineering, and control owners to shape data strategy, generate strategic insights, improve product decisions, and deliver rigorous analytics and machine learning solutions. Hire, develop, and retain data scientists and analysts while supporting innovation through business intelligence, experimentation, causal inference, and self-serve analytics.

Lead technical discovery, solution design, demonstrations, and proof-of-concept support for Anaconda’s AI and data science platform across EMEA. Partner with account executives on complex deals, create reusable technical content, represent customer needs to product and engineering, and coordinate with cross-functional teams through implementation handoff. Manage multiple opportunities independently while improving technical win rates, deal expansion, sales velocity, and regional pipeline development.

Lead pre-sales solution design and technical engagement for Sprinklr's AI-native Unified-CXM. Architect scalable contact center and data solutions, integrate AI and APIs, run technical workshops, POCs, and RFP responses, and collaborate with sales, consulting, and partner ecosystems to drive enterprise deals.

As a Senior Data Science Engineer, you'll lead data science projects, develop algorithms, analyze datasets, and mentor junior team members to enhance trading operations and strategies.

Develop and scale NVIDIA Inception’s European startup ecosystem by identifying, technically assessing, recruiting, enabling, and nurturing AI and accelerated-computing startups. The role advises founders and technical leaders on CUDA, NVIDIA SDKs, AI frameworks, GPU infrastructure, and platform adoption; leads technical workshops; translates ecosystem feedback into product insights; collaborates with venture capital firms and internal teams; and supports sales and enterprise customer motions. Travel across Europe is required approximately 40% of the time.

Build Paddle’s data science function and production decisioning systems from the ground up. Prioritize high-value use cases, personally deliver the first ML or agentic system, and own deployment, monitoring, experimentation, reliability, governance, and financial impact. The role will establish the production ML stack, collaborate across Product, Engineering, Risk, Finance, and Compliance, then hire and lead data scientists and ML engineers. Experience with regulated transactional domains, production ML operations, experimentation, and executive stakeholder management is required.

The Senior Product Owner (Data / AI) will be responsible for leading the development of data-driven product domains, collaborating with analytics and AI teams, defining product strategies, and ensuring the execution and delivery of data & AI product features.

The role offers veterans a one-week unpaid placement to learn about AI and data science in a leading UK tech company.

Lead and mentor a data science team building ML and LLM solutions for cybersecurity. Translate business needs into research and production ML objectives, prioritize roadmaps, collaborate cross-functionally, and drive technical vision, model development, and operationalization for malware detection and threat analysis.

The role involves guiding the Data Science team to develop search and recommendation systems, working with commercial teams to deliver user-focused products, and managing multiple projects related to data science implementation.

This role invites speculative applications for various tech positions. Candidates with skills in Salesforce, DevOps, AWS, and user experience are encouraged to apply.

As a Principal Machine Learning Engineer, you will design and develop scalable AI solutions, influencing company strategy and providing authoritative guidance on complex projects in the financial sector.

Provide technical leadership and architecture for defence-focused edge systems. Translate ambiguous customer problems into deliverable solutions for bids and delivery, ensure supplier assurance, assess hosting/integration options, manage technical risk, produce high-quality bid content, and support mobilisation and governance for consistent delivery.

Support the development, testing, evaluation, and productionization of AI/ML models and applications, including LLMs, agentic systems, document AI, forecasting, and optimization. Collaborate with engineering, product, business, and client stakeholders to translate requirements into technical work, establish performance metrics, maintain governance documentation, and monitor production systems for accuracy, cost, latency, and business impact.

Lead and grow the UK data organisation (Data Science, ML Engineering, Analytics Engineering, Data Engineering). Set strategy, priorities, and operating model; partner with product, commercial, clinical and ops stakeholders; drive international platform migrations (Databricks/Redshift to GCP), support new market launches, provide technical and architectural leadership, and build a high-performing team.

The Senior Product Manager will lead the strategy and development of the discovery experience for Ten's services, leveraging AI and data analytics for personalization, while mentoring junior team members and collaborating with cross-functional teams.

Lead end-to-end design and delivery of a global claims transformation program, translating business needs into technical requirements, coordinating cross-functional teams to implement automation and AI solutions, managing project plans, budgets, risk, and change adoption across international claims operations.

The Senior AI Transformation Consultant works with clients to identify AI opportunities, define robust business cases, and oversee AI project deployments, ensuring solutions deliver value.

Analyze and process very large business datasets using data mining and analytical techniques to uncover patterns and insights. Support business decision-making by identifying problems and discovering growth or efficiency opportunities.

Support and lead data-driven communications projects across EMEA and APAC, using NLP, statistical and ML methods to extract insights from multiple data sources, build pipelines, create visualisations and client-ready reports, and deploy AI-enabled solutions to inform reputation and communications strategy.

Lead and deliver advanced data and AI-driven communications solutions: design and implement analytics/ML approaches, integrate multiple data sources, build pipelines and visual reporting, manage and mentor data scientists, translate technical results for senior clients, support business development and innovate tools to advance corporate communications insights.