Top Python Jobs in London

Develop and optimise personal-loan pricing and trading strategies, automate pricing execution, identify pricing factors with modelling teams, and maintain management information for performance monitoring. The role provides analysis to senior leadership, supports regulatory compliance and fair customer outcomes, and acts as a commercial subject-matter expert while guiding supporting analysts. Strong SQL and experience with price comparison websites and risk-based lending pricing are essential.

Design, build, and operate scalable data pipelines, models, cloud platforms, and AI applications on Google Cloud. Lead technical delivery for client projects, make architecture decisions, manage risks, and ensure production quality through testing, observability, and data controls. Build and evaluate LLM applications, collaborate with consultants and data scientists, communicate with technical and non-technical stakeholders, and raise engineering standards through reviews, documentation, and reusable practices.

Supports application security tooling, vulnerability management, cloud security monitoring, secure design and API reviews, threat modeling, penetration-test triage, and engineering engagement. The role involves using tools such as Aikido and Prisma Cloud, reviewing code and CI/CD pipelines, maintaining security processes, and independently prioritizing security requests and remediation activities.

Build and operate production batch and streaming data pipelines across ingestion, transformation, reconciliation, and client delivery. Develop CDC, incremental loading, dimensional models, medallion datasets, data contracts, quality controls, monitoring, and CI/CD workflows. Support Snowflake, Databricks, SQL Server, and Azure platforms while improving architecture, security, tenant isolation, performance, and reliability. Investigate incidents and collaborate with product, valuation, client-facing, and technical teams.

As a Senior Data Scientist, you will lead the development of algorithms for payment solutions, working with cross-functional teams to enhance fraud prevention and payment success, utilizing advanced machine learning techniques.

Own the roadmap and delivery of Monzo’s internal controls and risk product platform. Build low-code prototypes, automated workflows, API integrations, AI-enabled tools, and real-time risk monitoring. Lead adoption across risk teams, guide two data and automation specialists, and partner with Product, Engineering, Data, Operations, and Risk stakeholders to replace manual control processes with scalable self-service solutions.

Graduate Analysts join Baringa’s consulting capabilities practice, supporting client and internal projects across customer experience, enterprise value creation, organisation and change, supply chain and procurement, and data, AI, solutions and engineering. Responsibilities include structured problem-solving, data analysis, collaboration, client communication, transformation delivery, and developing technical and commercial skills through formal training and hands-on work.

Graduate Analysts join Baringa’s Energy & Resources consulting practice, supporting client and internal projects across energy trading, energy products, markets and transactions, policy and regulation, and infrastructure transformation. Responsibilities may include quantitative analysis, data interpretation, market modeling, commercial and strategic analysis, technology-enabled transformation, and presenting recommendations to clients. The programme provides structured development, mentoring, and exposure to experienced consultants and international clients.

Conduct quantitative research for multi-strategy investment portfolios, focusing on alpha combination, allocation, portfolio construction, and capacity evaluation. Improve existing portfolios, manage daily portfolio and investment risk, develop portfolio construction methods, and collaborate with quantitative researchers, technologists, traders, and other research teams. The role requires strong analytical, statistical, machine learning, programming, large-data handling, and portfolio risk-modelling skills.

Join iSAM Vector as a Quantitative Researcher to design, test and implement systematic trading signals across global markets. Responsibilities include signal research, backtesting, model refinement, dataset and tool development, portfolio construction support, and communicating results to technical and non-technical stakeholders.

Ten-week internship combining financial research, client-facing support, and software engineering. Responsibilities include debugging Python, developing REST APIs and data pipelines, building Python libraries, deploying infrastructure and production code, monitoring systems, testing bespoke client solutions, supporting research functionality, clarifying requirements, and presenting product progress to stakeholders. The role requires independent problem-solving, cross-functional communication, and an entrepreneurial approach in a fast-paced capital-markets technology startup.

Designs, deploys, integrates, and maintains application security tooling across Bupa’s development environments. The role embeds security into CI/CD pipelines, supports infrastructure as code and DevOps practices, monitors tooling, investigates high-risk issues, automates controls, and provides application security expertise. It also supports regulatory compliance, assurance activities, evidence gathering, and communication with technical and non-technical stakeholders.

Build backend services, real-time data pipelines, operator-facing React applications, and secure Azure infrastructure for distributed radar systems. The role involves processing sensor data, designing scalable and resilient services, contributing to platform architecture, and collaborating with software, hardware, systems, and field operations teams. Based in London, the engineer will regularly collaborate with the San Francisco team and travel there approximately quarterly.

Develop scalable Python and Java solutions for generative AI and machine learning within Morgan Stanley’s trade surveillance analytics platform. Build agentic applications using LLMs, RAG, vector storage, MCP, and A2A patterns; integrate databases, UI frameworks, and DevOps practices. Collaborate with global Agile teams, translate business requirements, write comprehensive tests, optimize code and queries, and follow enterprise SDLC governance.

Own pre-sales technical activities for an AI security platform, including customer engagement, technical storytelling, proof-of-concept planning and execution, and supporting opportunities through the sales cycle. Collaborate with customers, sales, product, marketing, and engineering to translate requirements into solutions and messaging. The role also involves enterprise software deployment, MDM administration, live troubleshooting, competitive analysis, and helping customers adopt AI securely.

Build and operate real-time risk applications for PnL, VaR, greeks, dashboards, alerts, and monitoring. Responsibilities include full-stack development, Python backend and financial model integration, responsive frontend interfaces, DevOps, CI/CD, infrastructure, observability, incident response, AI-assisted development, LLM API integration, testing, and collaboration with quantitative and market risk teams.

Supports live trading systems by troubleshooting incidents, monitoring production environments, diagnosing anomalies, automating workflows with Linux, Python, and Bash, and coordinating with traders and developers. The role owns incident response, patching, recovery, documentation, stakeholder communications, and continuous process improvements to maintain reliable trading operations.

Build scalable data pipelines, platforms, datasets, and architectures supporting machine learning, analytics, pricing, forecasting, customer insights, and marketing decisioning. Use Python, Spark, Databricks, and cloud technologies to develop reliable, observable, cost-efficient data products. Partner with data scientists and machine learning engineers, operationalize models, improve engineering practices, mentor colleagues, lead technical designs, and collaborate with commercial stakeholders.

Lead the strategic architecture, development, governance, security, and operation of RES’s Microsoft Fabric and Azure data and AI platform. Design and deliver AI agents and services, establish engineering and evaluation standards, manage platform reliability and costs, and provide technical leadership in Python, SQL, APIs, software engineering, and LLMs. Partner with cybersecurity, vendors, executives, and global data teams to scale secure, governed AI capabilities across the renewable energy business.

Build, operate, and improve unified engineering platforms and core capabilities including Kubernetes, cloud infrastructure, CI/CD, observability, storage, and databases. Develop automation, tooling, APIs, and self-service mechanisms; manage platform services end to end; improve reliability, performance, security, and scalability; and support product teams through technical consultancy. Collaborate across multidisciplinary teams, contribute to architecture and roadmaps, and lead platform initiatives.

Investigate customer-reported issues across hardware, embedded software, connectivity, cloud services, and web applications. Reproduce failures, analyze logs and telemetry, communicate with customers, verify fixes, and build regression coverage. Test releases end-to-end under real-world conditions, identify systemic problems, improve observability, and create scripts, diagnostic tools, support tooling, and automation using AI-assisted development where appropriate.

Conducts client-focused analytics using credit reference data, statistical methods, Python, and SQL. Delivers credit strategy, model development, and bespoke analytical projects; analyzes multiple data sources, communicates actionable insights, and collaborates with internal and external stakeholders to develop commercial solutions.

Develop and test cloud-based full-stack applications and prototypes using Java, Spring Boot, Python, TypeScript, Angular, and Azure. Build REST APIs, integrate microservices and event-driven systems, create accessible responsive interfaces, contribute to CI/CD and automated testing, and apply secure coding practices. Collaborate with architects, data engineers, and UX designers during discovery-phase projects. The role requires active SC clearance and occasional travel to London.

Conduct research and quantitative analysis across wholesale financial markets using large regulatory datasets, including transaction-level trading and derivatives data. Develop reproducible analytical code, identify market risks, evaluate regulatory outcomes, and produce evidence-based insights for policy and supervision teams. Collaborate with market experts and stakeholders, communicate complex findings clearly, and contribute to both ongoing research projects and time-sensitive market analysis.

Join LSEG’s 12-month rotational Markets graduate programme, gaining exposure to financial risk, product research and testing, global market analysis, valuations, listings, and shareholder data. The role involves analyzing large datasets, coding or using business intelligence tools, drawing conclusions, proposing solutions, and collaborating across teams. Graduates receive structured development, industry qualification opportunities, group projects, and permanent employment from day one in a hybrid London-based role.