Top Python Jobs in London

Lead implementation of data-lineage and BCBS 239 compliance across risk, finance and technology. Own data governance, quality, metadata and reporting KPIs; manage cross-functional delivery, regulatory readiness, and stakeholder communications.

Lead product analytics for Wise Platform's Cash Management, building models, KPIs, dashboards and decision frameworks to drive liquidity, settlement and FX products. Deliver analyses, opportunity sizing, scenario modelling, and scalable data products to inform product roadmap and increase partner revenue and margins.

Join an agile front-office Commodities tech team to design, develop, and maintain trading applications. Work with traders, quants, and middle office to gather requirements, deliver scalable, resilient production code, troubleshoot outages, and collaborate globally while improving code quality and contributing to engineering communities.

Lead design and delivery of production-grade AI/ML solutions for Market Operations. Manage a team of data scientists and partner with engineering and business stakeholders to build, deploy, monitor, and govern models, establish best practices, and drive measurable operational impact.

Design, operate, and scale large distributed systems for telemetry processing. Build automation, use AI tooling to reduce toil, ensure availability and disaster recovery, participate in on-call incident response, troubleshoot production AWS/Kubernetes environments, and collaborate with application teams to meet SLOs/SLAs.

Design, build, and operate highly scalable real-time streaming microservices and data pipelines (Java/Python/Go) using Kafka, Flink/Spark on Kubernetes across multi-cloud and on-prem. Own design, deployment, monitoring, observability, and on-call support while improving platform reliability and developer experience.

Design and build end-to-end ML solutions for 1:1 personalization, own data transformation, model training and deployment, provide technical customer guidance, extend product capabilities, and shape BrazeAI strategy.

Design, implement, and operate discoverability and search features for the AISOAR marketplace. Lead end-to-end technical implementations, ensure high availability and security, troubleshoot platform issues, collaborate with customers and security partners, use observability tools, drive platform improvements, and participate in monthly on-call rotation.

The Engineering Manager will lead a Data Replay & Recovery Team to build a data replay application, improve service efficiency, and design a data platform for processing large datasets.

Design, architect, and develop scalable Go-based microservices and REST APIs for threat detection, case management, and incident response. Lead system design, own technical initiatives, mentor engineers, integrate AI/LLM capabilities, operate cloud-native services on Docker/Kubernetes and cloud platforms, participate in on-call rotation, and drive reliability and architectural improvements.

Build, operate, and scale CrowdStrike's global backbone and hybrid cloud networks. Design and implement IP and optical solutions, drive capacity planning, evaluate technologies, automate with IaC and CI/CD, support cloud networking, lead projects from ideation to implementation, and participate in 24x7 on-call rotation.

The Senior Quantitative Developer will enhance valuation models and risk analytics for structured finance products, collaborating with teams to develop marketing solutions for diverse client needs.

Lead and mentor data science teams to design, develop, and deploy ML and AI solutions (including GenAI/LLMs). Align technical outcomes with business goals, drive MLOps and model governance, and deliver scalable production systems.

The Senior Data Scientist will unify technical vision, develop and deploy ML models, and enhance AI strategy across teams. Responsibilities include collaboration, ownership of projects, and maximizing value through AI and data science techniques.

As a Quantitative Research Analyst Intern, you will model markets, develop algorithms, and conduct statistical analysis to enhance trading strategies.

Design, prototype, implement and optimize predictive models for sporting outcomes. Collaborate in an agile, multidisciplinary team, apply probability and machine learning methods, deploy models, and mentor junior colleagues.

Lead and manage a team of data scientists to design, build and deploy predictive sports models. Oversee algorithm development (probability, Monte Carlo, ML), mentor staff, collaborate with engineers and product managers, and ensure continuous delivery and high-performance, production-ready model implementations across multiple sports.

Lead independent liquidity and interest rate risk oversight for UK legal entities. Analyze balance sheet changes, monitor limits and indicators, challenge Treasury activities, prepare Risk Committee materials, support regulatory requests, and participate in second-line reviews, control assessments, and change management.

Lead client engagements while developing analytics strategies. Coach teams, analyze data, and create impactful business recommendations.

Build secure, scalable AI/ML platforms and applications to productionize research. Collaborate with AI researchers and data scientists, implement CI/CD and IaC, support experimentation environments, automate remediation, mentor junior engineers, and promote secure, responsible AI development practices.

Lead trading strategy development and execution for a commodities portfolio, manage risk, conduct analysis, and identify opportunities.

Lead development of the technical infrastructure to explain marketing growth drivers, automate insight generation, and productionise analytics tools (Lightdash, Streamlit, AI agents). Partner with marketing, regional, product, and analytics teams to identify opportunities, ensure data quality, and translate complex performance data into actionable strategies that drive execution and measurable impact.

Own end-to-end regulatory reporting datasets: map regulations to internal data, build and automate pipelines, implement data quality controls, create clear visualisations, investigate discrepancies, and partner with cross-functional stakeholders to ensure accurate, auditable reporting.

Lead analytics and data-science work for Localization: design and run A/B and causal experiments, build and deploy ML/NLP/LLM models at production scale, create scalable SQL/Python pipelines and dashboards, translate multilingual insights for stakeholders, mentor peers, and co-own metric frameworks and decision workflows.

Serve as the product owner between traders, quants, and engineering to deliver front-to-back technology solutions for commodities. Own backlog, translate business needs into requirements, maintain execution plans, ensure regulatory compliance, participate in testing/release sign-off, gather user feedback, and lead Agile ceremonies to drive continuous improvement.