Top Python Jobs in London

Build and improve quantitative models and forecasting tools for UK/European power markets, develop and implement algorithmic trading strategies, collaborate with traders, engineers and analysts to deploy production trading systems, support real-time trading decisions, and lead projects while mentoring junior team members.

Lead and grow a team of ~6 Solutions Engineers across UK, Ireland, Nordics, and Benelux. Drive technical wins in pre-sales, coach SEs, own technical evaluation through close, partner with Sales, Product, and Customer Success, recruit and ramp hires, and use AI and demo engineering to improve productivity and ROI.

Design, build and deploy autonomous robotic systems for real-world environments. Develop planning, perception and control systems, train and deploy ML models, integrate sensors/actuators, and drive long-term robotics strategy.

Lead statistical planning and analysis for oncology clinical programs, mentor colleagues, and drive innovation within cross-functional teams.

Work with large, messy enterprise datasets to apply LLMs and AI tooling, prototype AI-driven workflows, run large-scale analyses in Python/Jupyter, and collaborate with product and engineering to translate ambiguous operational problems into practical solutions.

Lead design, deployment and optimisation of personal lines pricing (focus on motor). Build and maintain pricing models, calibrate rating factors, develop pricing MI, monitor performance, and partner with Underwriting, Actuarial, Claims and Technology to ensure competitive, compliant pricing and governance.

Lead and develop the People Analytics data team, translate HR requirements into scalable data products, maintain data governance and quality, deliver dashboards and ad-hoc analyses (attrition, DE&I), and partner with HR, Finance and IT to ensure accurate, secure people data and technical strategy.

Build and operate production data pipelines and streaming integrations ingesting market data and asset telemetry. Partner with trading and data science teams to deliver data for forecasting models. Work with stakeholders to build integrations and analytical views and improve the data platform powering GAIA across the business.

Lead pre-sales technical engagements across Qatar and South Africa, advising C-level stakeholders on Data & AI strategy, designing complex solution architectures, building demos and reference assets, running workshops, and driving regional account growth and adoption of the Databricks platform.

Lead strategy and execution of analytics and AI/ML products to measure and maximize player lifetime value. Drive cross-team alignment, prioritize roadmaps, define experimentation and modelling standards, and ensure scalable, production-grade ML capabilities are adopted and deliver measurable business impact.

Lead FP&A analytics and commercial governance to protect profitability, reduce losses, and strengthen controls. Drive end-to-end AI use cases—from concept to production—using Microsoft Fabric and Azure tools to improve forecasting, scenario analysis, margin visibility, and decision support. Partner with FP&A and stakeholders to challenge assumptions, surface risks, and embed AI-driven FP&A workflows across the business.

Design, build and maintain Python-based systems and integrations for Risk, Finance & Compliance. Own end-to-end delivery: requirements, solution design, production deployment and support. Implement APIs, data pipelines, visualisations, data cleansing/enrichment, and platform improvements while collaborating with stakeholders and a small technical team.

Pre-sales Solutions Architect responsible for driving adoption of the Lakebase product line by partnering with Account Executives, designing and delivering technical solutions, workshops, demos, and customer collateral. Acts as a trusted advisor and tier-3 escalation for complex technical challenges, influences product roadmap with field insights, and collaborates with GTM, R&D, and GSIs to achieve strategic territory targets.

Join the Platform Core team to design, operate, and automate Depop's AWS-based infrastructure. Build and maintain Terraform/IaC, CI/CD pipelines, Cloudflare edge configurations, and platform tooling using Python/Golang. Mentor engineers, participate on-call, improve security posture, and drive platform reliability and developer self-service.

Responsible for BAU IFRS9 processes: produce and validate monthly outputs, implement and test model changes, maintain documentation and change logs, investigate model performance, and support credit analysis and stakeholder queries.

Design, build and automate scalable data pipelines, ETL/ELT and streaming ingestion on AWS (S3, Glue) and Snowflake. Ensure data modelling, testing, cleansing, monitoring, security and cost-efficiency while partnering with stakeholders and the data engineering community to embed modern data practices and deliver customer-focused solutions.

Design, build, test, deploy and maintain scalable identity services for a global fintech platform. Participate in full SDLC, drive architecture and code reviews, implement CI/CD and automated testing, collaborate cross-functionally, and mentor engineers while ensuring engineering best practices.

Design, build, and maintain automated test frameworks for embedded and connected medical devices. Define test plans for firmware, device drivers, APIs, connectivity, OTA updates, and WebUI. Integrate tests into CI/CD pipelines, collaborate with hardware/firmware teams, debug system-level issues, and validate device performance under real-world conditions. Must commute to London office 3–5 days/week.

Early-career AI engineer who ships production features rapidly using AI-augmented workflows. Own end-to-end features, prototype and evaluate LLM-driven solutions, collaborate with PMs and customer teams, pair with senior engineers, and maintain clear, tested, maintainable code while measuring impact.

Senior full‑stack Product Engineer owning end-to-end product areas: discovery, architecture, implementation, deployment, and customer adoption. Build scalable APIs, backend services, event-driven/streaming systems, and polished frontends while leveraging AI coding tools. Mentor engineers, champion testing, observability, CI/CD and infrastructure-as-code, and collaborate with product and commercial teams to deliver enterprise-grade document-processing features.

Architect and implement scalable generative-AI solutions for enterprise document workflows. Own end-to-end delivery from customer discovery through deployment, build advanced extraction and automation systems, ensure privacy/security by design, mentor engineers, and collaborate with product and commercial teams to drive customer adoption and measurable business value.

Support pricing and reserving activities by providing pricing analyses, performance monitoring, and technical pricing tool development. Work with underwriters and actuarial teams to monitor rates, ensure data quality, identify profitable opportunities, and comply with regulatory and risk management procedures. Develop technical skills and pursue actuarial qualification.

Lead development of behavioural features and detection algorithms from hypothesis to production using high-frequency GPS and inertial sensor data. Prototype, build scalable Python and SQL pipelines, evaluate ML and rule-based models, run experiments, and collaborate with engineering, product, and actuarial teams to integrate features into pricing and measure impact.

Lead a global team to define and deliver an enterprise network automation product roadmap. Build a scalable, secure IaC/GitOps platform to automate WAN, LAN, data center, firewalls, load balancers and DDI. Drive DevOps, CI/CD, security-by-code, and cross-functional alignment to reduce manual toil and accelerate service delivery in a low-latency financial markets environment.

Lead Marketing Analytics by defining the analytics roadmap, prioritizing business questions, and shaping measurement frameworks (experimentation, attribution, MMM). Partner with Marketing, Product, and Strategy to monitor KPIs, translate analysis into decisions, and hire, coach, and develop a team of Data Scientists to improve marketing outcomes.