Top Python Jobs in London

The role involves developing and maintaining Python micro-services for a proprietary trading platform, collaborating with traders and global teams, and integrating with analytics libraries.

Design and validate automated workflows for assays, support lab automation systems, troubleshoot equipment, and lead project collaborations in R&D.

The ETL Test Engineer analyzes business requirements, creates test cases, develops validation scripts for automated testing, and ensures data quality across multiple systems and teams.

Lead technical onboarding of customers onto the DigitalGenius platform: build automation flows, fine-tune AI behavior, integrate via APIs/webhooks, run trainings, troubleshoot issues, and manage projects to ensure timely implementations.

Provide technical leadership for subsea pipeline, riser and tie-in spool design across project phases (pre-FEED to decommissioning). Perform mechanical analyses, check calculations, prepare and review deliverables, contribute to bids, represent the business in meetings, and support technology development and global coordination.

Own and operate the internal platform for engineering: design and run Kubernetes and bare-metal infrastructure, automate via Terraform/Ansible and scripting, build CI/CD and self-service tooling, optimise networking and storage for ML/hardware workloads, implement monitoring and security (IAM, secrets, threat detection), and drive reliability and continuous improvement.

Operate and maintain daily VaR and margin systems, monitor intraday exposures and limits, reconcile margins, run stress tests and liquidity models, investigate anomalies, validate P&L attribution, and produce risk reports for senior management while collaborating with traders to optimize margin and limit usage.

Own and operate cloud production infrastructure (GCP/AWS), manage Kubernetes clusters, automate via IaC (Terraform/Pulumi/Ansible) and CI/CD, build and monitor data pipelines (Argo), perform SRE incident response and level-2 support, and collaborate with data scientists and engineers to improve platform reliability and scalability.

Design and build Azure-based AI platform capabilities for agentic AI. Create standards, templates and reference implementations for LLMs and agents, ensure secure model access, observability, LLMOps, CI/CD, governance, and reliable production operation.

Design and industrialise production-grade LLM systems and reusable AI platforms on Azure. Build RAG pipelines, agentic workflows, orchestration, evaluation and observability frameworks, and safety guardrails. Optimize for performance, cost and reliability while enabling horizontal reuse across squads and embedding AI risk controls.

Graduate analytics role on the London trading floor delivering data-driven market insights. Responsibilities include pre/post-trade analysis, supply/demand and trade-flow modelling, vessel tracking impacts, building forecasting models with traders, anomaly detection, and communicating findings to traders and senior management.

Design, build, and operate automation-first internal platforms and tools for pre-sales. Troubleshoot security, network, and system issues; manage firewall policies; develop integrations and APIs using Python (Django) and Ruby on Rails; produce documentation and runbooks; collaborate with stakeholders to secure and scale solutions across Linux, Windows, and macOS environments.

Front-office quantitative role supporting mortgage and ABS trading across European markets. Build and implement mortgage pricing, loan-level cashflow and recovery models, automate pricing/surveillance frameworks, and work closely with portfolio managers on complex non-agency and illiquid securitized assets.

Build and maintain automated data pipelines on the Databricks lakehouse using SQL, Python and PySpark. Produce production-ready data models, implement data quality checks and tests, follow Git/GitHub workflows, collaborate with consultants on healthcare data problems, and learn best practices from senior engineers.

Lead the credit strategy for second charge mortgages, defining credit policy, developing risk models, and collaborating across functions to optimize lending processes while maintaining portfolio quality.

The Quantitative Analyst will analyze trading behavior, collaborate with teams, and improve trading strategies using data and skills in Python and C#. Attention to detail and prioritization are essential for success.

Consult as a data scientist to design, build and deliver advanced analytics and ML solutions across the full modelling lifecycle. Translate client needs into analytical approaches, perform exploratory analysis, develop and test models, and handover solutions using tools like Python, SQL, Databricks and visualization platforms.

Work on platform engineering to build, automate and maintain cloud infrastructure and platform components; support operational excellence through on-call rotations, incident management, CI/CD, monitoring, and BAU; collaborate with engineering and data teams to design secure, scalable systems and reduce operational toil.

Build and operate the AI Portal SaaS platform: develop services, APIs, integrations and UIs; improve reliability and observability; triage and resolve production incidents; participate in on-call rotation; deliver end-to-end product features for internal and partner customers.

Design end-to-end conversational experiences for Spotify's AI products, including dialogue flows, prompt engineering, LLM prototyping, evaluation frameworks, safety guardrails, and cross-functional collaboration to improve conversation quality and user task completion.

Design, build, and maintain end-to-end data ingestion pipelines and data architecture. Transition datasets to a new stack, map/standardize/normalize data, monitor data quality, manage vendor data inputs, and partner with commercial trading teams to gather requirements and support analytics and investing use cases.

Manage and scale systematic trading strategies for global agricultural commodities by combining fundamental research with quantitative modeling, alternative datasets (weather, satellite, logistics), rigorous backtesting, portfolio construction, risk management, and productionalizing research into live trading systems.

Own cloud architecture intelligence and cost optimization: analyze cloud spend, identify inefficiencies, build dashboards, enforce governance, partner with engineering/finance to drive cost-conscious design and operations.

As a Senior Backend Engineer, you'll develop features using Python and various AWS services, focusing on AI-driven solutions for the insurance sector.

Design, build, and maintain scalable automated workflows and integrations using platforms like n8n, Zapier, Make, or Workato. Integrate systems via APIs/webhooks, troubleshoot workflow issues, monitor performance, document processes, and support data synchronization across CRMs and business tools while collaborating with cross-functional teams.