Top Python Jobs in London

Lead and develop a team of Data Analysts responsible for Citymapper’s regional data quality and reliability. Own data strategy, partner with Product, Engineering, and Operations on priorities, improve workflows and automation, and translate complex datasets into actionable product insights. The role requires strong people leadership, project management, cross-functional communication, and comfort working with technical teams and ambiguous operational challenges.

Build and maintain shared Python services, frameworks, data pipelines, and APIs powering AI products. Design scalable AWS-based SaaS platforms, data ingestion and processing systems, and integrations with internal and third-party services. Improve platform security, observability, testing, CI/CD, documentation, and monitoring while collaborating with product teams and mentoring engineers.

Build and ship AI-powered requirements features, including drafting, consistency checks, impact analysis, intelligent suggestions, and agentic workflows. Integrate and evaluate language models while optimizing reliability, latency, cost, observability, and safety. Develop supporting infrastructure such as data pipelines, evaluation harnesses, prompt and model management, and guardrails. Work across backend, APIs, and UI, partnering with product and customers to prototype, validate, and productionize solutions.

Build and ship core AI customer-service product features across Python, TypeScript, cloud infrastructure, event-driven systems, and integrations. Own solutions from customer discovery through delivery, balance rapid MVP development with scalable foundations, and improve testing, documentation, reliability, and security. Collaborate directly with customers and stakeholders while contributing across frontend, backend, infrastructure, and AI product development.

Build and ship core AI product features across frontend, backend, infrastructure, and integrations. Work directly with customers to scope solutions and deliver outcomes, balancing rapid MVP development with scalable foundations. Establish best practices for testing, documentation, reliability, and security while contributing to a fast-moving founding engineering team.

Build and ship AI voice-agent products across Python, TypeScript, cloud infrastructure, and event-driven systems. Design agent orchestration, prompting, tool calling, and speech pipelines; create evaluations, monitoring, and feedback loops; improve reliability; and work directly with customers to scope and deliver solutions. The role also involves full-stack development, third-party integrations, technical ownership, and establishing engineering best practices.

Own technical relationships for strategic EMEA accounts and US technology partners. Lead complex evaluations, integrations, trials, workshops, RFPs, proofs of concept, demos, escalations, and regulatory certification demonstrations. Guide developers and architects through APIs and SDKs, support revenue retention and expansion, influence product strategy, identify product gaps, and mentor Solutions Engineers globally. Coordinate cross-functionally with Sales, Product, Customer Success, Onboarding, Engineering, and partner teams while supporting occasional US and EMEA travel.

Lead end-to-end machine learning and AI initiatives, from problem framing and experimentation through deployment, monitoring, and iteration. Build production ML models, LLM-powered solutions, pricing and propensity models, recommendations, and operational automation. Partner with Commercial, Marketing, Product, Finance, Engineering, and Operations stakeholders, connect models to business outcomes, establish best practices, and mentor junior data scientists.

Paid 10-week actuarial internship in London involving large-dataset analysis, actuarial models and simulations, risk pricing, client presentations, reports, meetings, and RFP-related business development. Candidates should be in their penultimate year of a numerate degree, have strong mathematics ability, interest in insurance and risk, analytical problem-solving skills, and clear communication. Programming experience with Python, R, or VBA is beneficial but not required.

Manage multi-asset investment strategies, construct portfolios, evaluate portfolio risk, research investment managers, develop investment strategies, and contribute to performance. The role also involves communicating investment views to clients and consultants, supporting marketing initiatives, delivering strategic projects, and collaborating across investment disciplines.

Lead daily and ad hoc asset-liability management responses and own weekly ALM management information for Institutional Retirement Finance. Review interest rate and inflation exposures, explain profit and loss movements, assess impacts of trades, assets, pension risk transfer schemes, and reinsurance, and communicate insights to stakeholders. The role also strengthens reporting controls, governance, documentation, systems integration, and automation. Candidates should be nearly or newly qualified actuaries with strong investment, ALM, actuarial reporting, Excel, and data analysis skills.

Deliver complex blockchain and digital asset consulting engagements, including technical investigations, blockchain analytics, fund-flow tracing, smart contract and platform reviews, risk frameworks, due diligence, client reporting, research, proposals, and project management. Support client relationships, business development, thought leadership, solution development, budgeting, scheduling, and delivery of high-quality investigative and advisory work.

The Senior Sales Analyst will deliver sales performance reporting, analyze funnel trends and root causes, build forecasts and business cases, optimize measurement, strengthen KPI and data-quality foundations, and provide commercially focused recommendations. The role partners with Sales, Customer Success, BI, Data & Transformation, and leadership teams, tracks implementation outcomes, and leads high-impact ad hoc analysis. Advanced Excel, intermediate SQL, and Tableau or Power BI expertise are required.

The Staff Engineer will lead architectural design for researcher operations systems, integrating SaaS components, and managing technical strategy while collaborating across teams.

Lead and grow the Human Influence engineering function, managing research and software engineers while delivering an engineering roadmap. Design scalable evaluation and benchmarking systems, automated human-AI experiment pipelines, multi-agent study toolkits, data pipelines, reinforcement learning environments, and large-language-model fine-tuning projects. Translate research questions into reproducible production engineering tasks, collaborate with technical and nontechnical stakeholders, and lead projects from scoping through deployment or publication.

Research Engineer developing AI safety methods focused on human influence. Responsibilities include fine-tuning and post-training LLMs with reinforcement learning, building scalable evaluation and benchmarking pipelines, designing RL environments, applying interpretability techniques, deploying containerized ML systems, and conducting engineering-heavy research on large compute clusters.

Lead end-to-end Veeva Vault CRM implementation and migration projects for life sciences customers. Serve as a technical authority and advisor to senior stakeholders, guiding architecture and best practices, configuring solutions, resolving complex technical issues, mentoring teams, and supporting implementation partners. Work independently across multiple assignments in a remote environment while exploring new technologies and AI tools. The role requires approximately 20% travel and fluency in English.

Designs, builds, and maintains global Azure infrastructure using Terraform and automation. Manages Entra ID, networking, firewalls, privileged access, Microsoft 365, SaaS platforms, and endpoint tools including Intune and Kandji. Develops Python, PowerShell, and Power Platform automations, explores AI-driven infrastructure operations, supports compliance, and provides senior technical leadership, troubleshooting, documentation, and change control.

Six-month Data Science and Marketing Effectiveness internship analyzing large datasets, building marketing mix models, forecasting tools, customer segmentation, and econometric or machine learning models. The intern will use Python and related analytics tools, translate findings into client recommendations, participate in consulting projects, and complete an individual R&D project. The role is hybrid in London and requires full UK work authorization without sponsorship.

Researches and assesses cyber threats, tracks threat actors and adversary tactics, and produces actionable intelligence for technical, operational, and executive audiences. The role applies the MITRE ATT&CK framework, open-source research, structured analysis, and intelligence lifecycle practices. It supports threat hunting, detection engineering, vulnerability management, and incident response while translating intelligence into improved security controls and maintaining relationships with internal teams, industry peers, and intelligence-sharing communities.

Own Modo Energy’s Nordic market coverage across Sweden, Finland, Denmark, and Norway. Publish research on battery storage revenues, buildout, and market design; automate data ingestion; create asset registers and market benchmarks; and support Nordic forecasting products. The role also involves training an AI analyst, collaborating with engineering and forecasting teams, and serving as the customer-facing market expert for Nordic energy markets.

Build and maintain cloud-native platforms and tools that enable rapid, secure service provisioning. Apply site reliability practices across distributed systems, debug production issues, write maintainable code, and improve architectural patterns. Operate cloud and Kubernetes platforms, automate infrastructure and software delivery through CI/CD, use observability tools, develop Infrastructure as Code modules, document solutions, and support engineering teams adopting reliable operational practices.

Senior Site Reliability Engineer responsible for maintaining and improving production infrastructure supporting cloud-based core banking and payments platforms. Duties include designing resilient systems, disaster recovery, backups, redundancy, capacity planning, automation, observability, on-call support, production maintenance, documentation, and reliability-focused product development. The role also involves mentoring engineers, collaborating with product teams and customers, and managing complex fleet operations across SaaS environments.

Lead technical direction for an AI platform connecting workloads to multiple LLM providers. Build API gateway and routing infrastructure, agent orchestration, capability lifecycle tooling, access controls, API key management, caching, cost and latency optimization, adoption analytics, and trust, safety, and governance controls. Define API standards and promotion workflows while supporting auditable, scalable AI services across client engagements.

Conduct portfolio and risk management for a new systematic multi-strategy trading platform. Build portfolio analytics and monitoring infrastructure, onboard quantitative strategies, improve platform operations, and support production on a rota. The role requires quantitative research experience, strong Python skills, expertise in statistics, probability, portfolio construction, and risk management, plus the ability to connect empirical research with practical investment implementation.