Top Python Jobs in London

Lead EMEA Trade & Working Capital portfolio strategy, risk management, and governance. Drive pricing, capital and liquidity optimization, committee decision-making, underwriting standards, stress testing, forecasting and KPIs, and regulatory compliance. Partner with product, sales, risk, finance, compliance and operations to improve returns and reduce volatility across trade products.

Lead design, development, testing, release, and production support for Equity Derivatives workflows. Own production outcomes, incident triage, stakeholder communication, UAT, architecture and observability. Drive adoption of AI-assisted engineering practices, maintain release discipline, gather telemetry for stability metrics, and improve system reliability and coding hygiene through cross-functional collaboration.

Lead applied AI/ML efforts to design, build, deploy, and maintain production ML services (NLP/CV focus). Collaborate with engineering, cloud, and SRE teams, research models, ensure MLOps best practices, and document processes for regulatory compliance.

Lead design, development, and delivery of risk, pricing, trade capture, and commodities operations software. Collaborate with trading, quant, sales, and middle office to produce secure, high-quality production code, provide technical guidance, and drive product and architecture decisions. Promote cross-team collaboration, firmwide engineering practices, and mentor engineers to deliver scalable solutions.

Lead and perform hands-on penetration tests across applications, infrastructure, and cloud; design assessments and simulations; evaluate controls; produce detailed findings and remediation guidance; collaborate with cross-functional teams and apply threat intelligence to improve security posture.

Build and maintain Novas core Python frameworks and calculation engine for loan-loss forecasting (CECL, IFRS9, CCAR). Implement high-performance numerical algorithms (NumPy, Pandas, DuckDB), champion TDD, translate stakeholder needs into production-quality designs, perform code reviews, debug model forecasts, and document technical decisions while collaborating with researchers, governance, and business teams.

Conduct applied AI research to develop novel algorithms and large-scale ML models, run experiments and statistical analyses, collaborate with data scientists, engineers, and business stakeholders, and contribute to production applications, open-source, and patents in the financial domain.

Cover Sweden and Norway macroeconomies: produce forecasts, monitor monetary/fiscal/political developments, publish client notes, engage clients, attend calls/conferences, travel to Nordics, and collaborate with FX and rates teams.

Lead design and delivery of applied AI/ML solutions for data management and governance. Build prototypes, collaborate with business and engineering teams, document models and experiments, present results to stakeholders, and adopt emerging LLM/ML techniques to drive transformation.

Design, build, and maintain large-scale, secure data engineering solutions. Lead architecture, deliver production code, drive automation and operational stability, mentor teams, and evaluate vendor/technology choices to advance risk technology platforms.

Lead design and deliver IAM-focused public cloud platform services across AWS/Azure/GCP. Architect, implement, and operate secure, reliable production software; drive automation, CI/CD, and operational stability; lead design reviews, mentor engineers, and collaborate across platform and trust teams.

Build AI/ML-driven analytics and automation for CIB Treasury, Securities Services and Payments. Develop scalable data architecture, automate manual processes, create sequential decision-making tools to optimize net interest income, drive projects end-to-end from prototype to production, present commercial recommendations to stakeholders, and collaborate across Quant Research, Treasury, CIO, Technology and CDAO.

Support IRRBB and FTP analytics for the CIB by building automation, reports, dashboards and quantitative tools. Validate modeling assumptions, produce executive-ready analytics, respond to treasury and LOB queries, strengthen governance and documentation, and support audits, model governance and regulatory requests.

Lead design and delivery of production-grade AI/ML solutions for Market Operations. Manage and mentor a team of data scientists, partner with AI engineering and stakeholders, ensure robust MLOps, model governance, deployment, monitoring, and documentation while driving measurable operational impact.

Lead development of cloud-native Python applications for global commodities trading desks. Design, build, test, and operate resilient, secure production systems; drive automation and CI/CD; evaluate vendor solutions; and mentor engineering communities of practice.

Design, build, and operate cloud-native lakehouse and streaming data platforms and pipelines using Python, PySpark, dbt, Airflow, and orchestration/infrastructure tooling. Ensure performance, reliability, security, and observability; model and transform data for analytics; deploy with IaC, containers, and Kubernetes; mentor engineers and drive platform standards and best practices.

Design, build, and productionize autonomous and assistive multi-agent AI systems. Implement RAG and semantic search with vector databases, integrate tools/APIs, apply prompt engineering and guardrails, orchestrate microservices workflows, instrument agents for metrics, run evaluations/A-B tests, and mentor teammates.

Support global fixed income index research by analyzing large datasets, building quantitative models, managing client projects, maintaining index operations, evaluating performance and market trends, and producing visualizations and reports to inform strategic product decisions.

Lead strategy and delivery of agentic AI across the Commercial & Investment Bank: design, build, and productionize multi-agent systems and RAG pipelines; integrate tools and cloud deployments; implement evaluation, safety, and observability; partner with stakeholders to deliver business impact; and mentor teams on LLMs, agent frameworks, and best practices.

Lead product development for equity derivatives trading platforms: define business purpose, write and validate specifications (Margin Loans, Financing, Convertible Bonds), align technology investments, manage delivery and governance, engage traders/quants/tech/compliance, and assess emerging trends. Collaborate globally and support occasional international travel.

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.

Lead integration and DevOps work for a low-latency equities onboarding team: participate in requirements, design, development, production rollouts, integration testing, release management, and automation using Linux, Python, shell scripting, networking and FPGA technologies to ensure stable, high-quality deliveries.

Lead development of equities algorithmic trading strategies and execution platform. Build simulation and automated testing, analyze and improve strategy performance, troubleshoot production issues, and develop scalable real-time processing and automation to improve operational stability.

Lead engineer designing, developing, and troubleshooting ultra-low-latency electronic trading systems. Write high-quality C++14 production code for multithreaded, networked applications, collaborate with traders and cross-functional teams, lead engineering practices, participate across the SDLC, and drive automation and stability improvements for order routing, matching engines, market access, and risk systems.

Lead development of large-scale, real-time and historical market-data applications using KDB/Q. Drive system design, coding, performance optimization, scalability, high availability, and CI/CD automation. Mentor team members, manage delivery, partner with stakeholders and support teams, and help migrate and re-architect systems to AWS while improving operational stability and testing practices.