Top Python Jobs in London

Lead design and implement IAM-focused public cloud platform services. Develop and maintain production code, drive architecture and reliability, automate remediation, lead reviews, mentor engineers, and collaborate across platform and trust teams to deliver secure, scalable cloud services.

Lead Site Reliability Engineer responsible for improving reliability, scalability, observability, and resiliency across AWS platforms and applications. Designs monitoring and alerting frameworks, establishes SLIs, SLOs, and error budgets, leads major-incident response, conducts resiliency reviews, and resolves production bottlenecks. The role also drives CI/CD quality automation, containerized operations, AI-assisted incident workflows, security controls, knowledge sharing, and adoption of cloud, infrastructure-as-code, chaos engineering, and distributed tracing practices.

Lead AI controls enablement by translating AI risks into practical controls, partnering with Controls, Business, and Technology to design scalable solutions, perform risk reviews, implement controls, and advise senior stakeholders to ensure compliant AI adoption.

Develop and validate quantitative models and algorithms for risk and treasury operations. Responsibilities include data analysis, backtesting, model assessment, software and tool enhancement, financial optimization, and collaboration with internal teams. The role involves applying academic quantitative knowledge to banking, financial instruments, and global markets while proposing solutions to complex modeling challenges.

Leads software engineering for JPMorganChase’s wholesale credit risk technology team. Responsibilities include developing and reviewing secure Python code, guiding technical teams, designing scalable cloud-native systems, and establishing enterprise governance for AI-assisted engineering. The role sets toolchain architecture, CI/CD quality gates, automation standards, responsible AI controls, and validation requirements while serving as a firmwide software development lifecycle subject matter expert.

Lead infrastructure engineering for critical market data platforms: provide production support, implement changes, lead architecture and automation workstreams, validate AI-assisted recommendations, ensure performance, resilience and data quality, and collaborate across platforms to modernize and stabilize trading market data infrastructure.

Partner with XVA trading and counterparty credit risk to design, develop, and deploy quantitative models and analytics for pricing and risk management. Translate business needs into solutions, provide production support, own implementation with Technology, and drive model governance and validation.

Support planning and automation for the orderly wind down of trading and derivative activities. Prepare regulatory submissions, develop analytics and methodologies, automate processes with technology partners, produce materials for senior stakeholders, and assist capability leads to enhance regulatory readiness and local recovery planning.

Conduct quantitative research for risk and treasury operations by analyzing data, backtesting strategies, developing and validating mathematical models, assessing model risks, and improving software tools. Collaborate with internal teams to optimize financial solutions across asset classes and instruments while presenting complex quantitative concepts clearly. The role is designed for PhD students and offers practical financial modeling experience with potential full-time opportunities.

Supports quantitative risk and treasury research by analyzing data, backtesting strategies, maintaining software tools, evaluating model soundness, and developing, validating, and enhancing mathematical models and algorithms for financial applications.

Supports end-to-end technology audits for consumer banking, including risk assessments, control testing, workpaper documentation, reporting, and issue closure verification. Uses data analytics and AI-enabled audit tools to identify risks and evaluate governance, risk management, and technology controls. Collaborates with stakeholders, communicates findings, monitors regulatory developments, and contributes to improving audit execution and control frameworks.

Lead design, operation, and reliability of large language model serving infrastructure. Build backend services, deploy and lifecycle-manage LLMs on cloud and GPU clusters, implement observability, tune performance/cost, run incident response/on-call, and drive AI-assisted engineering and safe-responsible AI practices.

Develop and maintain data pipelines and business applications to support model risk governance. Implement model performance monitoring, workflow automation, and LLM-enabled solutions using Python and web frameworks. Emphasize data controls, testing, AI-assisted development tooling, and collaboration with cross-functional stakeholders to deliver secure, reliable analytics and efficiency tools.

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.

Produce daily T+1 P&L and market risk reports for equity derivatives, analyze P&L drivers, coordinate control issue resolution, support month-end close, implement robust controls, and respond to ad hoc requests. The role partners with Front Office, Risk, Valuation Control, Finance, Operations, and Technology while improving reporting workflows and accuracy.

Lead development of secure, scalable identity and access management services for public cloud platforms. Responsibilities include architecture, system design, production software development, reliability improvement, automation, design reviews, cross-team collaboration, technical leadership, and mentoring. The role requires cloud-native engineering experience, IAM or entitlement governance expertise, proficiency in languages and infrastructure technologies, continuous delivery practices, and a strong focus on security, resilience, and developer experience.

Develop, test, and deploy software solutions for automated trading systems in partnership with Quantitative Researchers. Implement high-performance, scalable systems using advanced quantitative techniques, distributed computing, ML/NLP, and strong software engineering practices. Collaborate on priorities, deliver custom solutions, and engage with senior team members during an 11-week internship.

Leads the Verification Data Science team supporting KYC onboarding and document verification. Owns the data science roadmap, guides machine learning projects, manages image and tabular datasets, develops deep learning models, optimizes production performance, and maintains Python systems. Coaches and develops data scientists, collaborates with cross-functional stakeholders, communicates technical impact, and researches methods to improve verification and prevent criminal activity.

Lead private company coverage of fintech and payments firms: conduct fundamental research using traditional and alternative data, build models, write and market research notes, advise clients, build industry relationships, and coach junior analysts. Requires fintech/payments domain expertise and advanced data/market tool proficiency.

Deliver technical training to clients and partners, create and maintain courses and video content, support certification assessments, enable external delivery partners, and keep documentation current. The role requires explaining technical SaaS products, APIs, programming concepts, pricing models, and AI tooling to varied audiences while collaborating with Product, Customer, and Partnerships teams.

Build and operate Wise’s global cloud-based database platform, automation, and tooling. Responsibilities include designing scalable infrastructure, developing migration and recovery strategies, embedding security controls, improving reliability, leading incident response, mentoring engineers, influencing roadmaps, and supporting on-call operations. The role requires strong platform engineering, cloud infrastructure, Python, DevOps tooling, and distributed database expertise, with YugabyteDB experience preferred.

Lead product direction and build agentic AI systems for autonomous merchandising optimisation: prototype multi-agent flows, take prototypes to production, define trust/governance, drive measurable experiment throughput and conversion uplift, and partner across engineering, data science, and brand teams.

Build and deploy production-grade LLM applications spanning backend services, data orchestration, vector search, and front-end integrations. Work directly with strategic customers in agile sprints, integrate legacy systems, create reusable AI libraries and scaffolds, and influence platform strategy through field-tested solutions. Lead implementations from concept to production while ensuring scalability, security, observability, and performance.

Own marketing analytics reporting and infrastructure that explain growth drivers and identify high-value opportunities. Develop automated insights, Marketing Financials tooling, Lightdash reports, Streamlit applications, semantic layers, impact calculations, and AI-enabled workflows. Partner with marketing, analytics, product, and regional teams to convert insights into execution, while improving prioritization, collaboration, data quality, and analytics team processes.

Lead customer value journeys for Celonis, translating strategic priorities into process-improvement use cases, business cases, demos, prototypes, workshops, and transformation roadmaps. Advise on IT and AI strategy, use SQL or Python for prototypes, identify realized value, drive adoption and expansion, manage projects, and present outcomes to senior and C-level stakeholders. The role partners with Sales, IT teams, and ecosystem partners across finance and supply chain transformations.