Top Python Jobs in London

Conduct forward-looking risk analysis on equity portfolios across EMEA, lead investment risk reviews, monitor compliance with internal guidelines, enhance risk tools, and provide quantitative insights to product and client teams to support investment decisions.

Manage LDI and derivative portfolios, construct hedges against liabilities, monitor risk and performance, oversee OTC derivative trades, develop market views and products, prepare client communications, and maintain relationships with trading desks and stakeholders.

Apply and develop statistical and ML methods for genomics and multi-omics data to support target discovery and validation. Build scalable, reproducible computational workflows, integrate human genetics with OMICs, collaborate with experimental and ML teams, communicate results, and contribute to scientific outputs.

Lead the ESG Data Product roadmap and backlog, translate business needs into product requirements, partner with engineering and data architecture to build scalable, governed ESG data capabilities, onboard vendors, monitor data quality, and drive adoption of enterprise data standards.

Design, implement, and evaluate production ML models for ETA, destination, and product estimation using maritime AIS and geospatial features. Build dbt features orchestrated by Airflow, run structured experiments with the kpler-ml framework, log and compare runs in MLflow, monitor model drift, and collaborate with market analysts to prioritize improvements.

The Senior Infrastructure Engineer leads infrastructure management and cloud architecture initiatives, managing both Apple and Windows estates while mentoring junior engineers and enhancing automation solutions.

Build and operate backend services, data pipelines, and operator-facing web apps that ingest, process, and present real-time radar sensor data. Design secure, scalable Azure cloud infrastructure and instrumentation, influence platform architecture, and collaborate with hardware, systems, and field teams to deliver resilient, low-latency distributed systems.

Serve as a trusted technical advisor and sales engineer, driving enterprise opportunities through demos, PoCs, deployments and adoption. Partner with Sales, Customer Success and Partners to translate technical solutions (Neo4j, Terraform, Kafka, APIs, IAM) into business value and support customers across the lifecycle.

Lead full‑stack product delivery for B2B features with backend emphasis: design APIs, own architecture, ship production systems, ensure testing/observability, and partner with product and platform teams to support demos, trials, and customer onboarding.

Lead CuspAI's data strategy and team to acquire, generate, curate, and deliver ML-ready materials data. Build partnerships, prioritize data investments, oversee data-generation programs, set quality/provenance standards, and act as single point of accountability for research data commitments.

Lead design, experimentation, and production of large-scale retrieval and ranking systems for Microsoft 365 Copilot. Drive semantic, dense, sparse, and hybrid retrieval, RAG and LLM-integrated architectures; define evaluation metrics, partner with engineering and research, mentor teams, and ensure privacy, scalability, and customer relevance for search, chat and agent experiences.

Perform software safety lifecycle tasks: hazard analyses (HARA, FMEA, FTA, STPA), derive and trace software safety requirements, review C++/Python/ROS code, define fail-safes, collaborate across teams, and support safety cases for airport deployment per ISO 26262 and SOTIF.

Lead development of globally consistent short-tail property pricing model specifications, collaborate with underwriting to standardize technical pricing, support reinsurance strategy and planning, produce performance monitoring and MI, and leverage data assets and predictive modeling to improve portfolio management.

Lead and grow multiple engineering teams delivering personalization, search and recommendation systems. Set technical strategy, ensure reliability and SLI/SLOs, drive DevOps and CI/CD excellence, partner with Product and Data Science, hire and develop engineering leaders, and own product-group outcomes.

Design and implement automation and reporting solutions for Controllership using Python, Power BI, and Microsoft Fabric. Build reconciliations, dashboards, controls, and drive finance transformation while partnering with stakeholders across Finance, Risk, Compliance, Technology, and Data.

The Head of Software Engineering will lead and inspire teams, driving technical excellence, innovation, and agile practices while delivering complex systems and solutions for personalisation and customer-centric environments.

Lead market risk oversight for an energy trading desk across gas, power and renewables. Quantitatively analyse deals, improve VaR, stress testing and option pricing methodologies, support digitisation, and build relationships with front office while managing junior staff and integrating risk into new products and processes.

Lead identification, design, and implementation of automation and reporting across Controllership. Build Python solutions for data collection, reconciliation and controls; develop Power BI/Tableau dashboards; support Microsoft Fabric and evaluate AI/Copilot use cases. Partner with stakeholders, drive continuous improvement, document solutions, and provide training to increase automation and operational transparency.

Lead and own end-to-end development of revenue-critical full-stack systems: define problems, design architectures, make pragmatic trade-offs, deploy and ensure production reliability, and translate technical constraints into business impact. Work across backend, frontend, and infra, mentoring teams and using AI-assisted tools to accelerate delivery.

Build and own end-to-end full‑stack features: implement, test, deploy, and maintain production code. Collaborate in pair programming and code reviews, use modern tooling (including AI-assisted tools), and prioritize product-focused solutions with clean, maintainable implementation.

Partner with sales and channel teams to present Snowflake, run demos, proofs-of-concept, and design implementations; build technical champions, articulate data architecture and cloud solutions, and collaborate with product, engineering, and partners to drive deals and customer success.

Lead technical pre-sales efforts for UK accounts: present Snowflake to technical and executive audiences, build demos/POCs, develop technical champions, collaborate with sales, partners, product and engineering, and represent Snowflake at events to drive deal wins and implementations.

Lead the design, build, and productionisation of Fundment's AI systems and infrastructure on GCP. Define AI strategy, architect LLM/RAG/agent solutions, implement MLOps, model governance, IaC, monitoring, cost optimisation, and mentor a multidisciplinary team to embed AI into products and operations.

Work with quantitative researchers and portfolio managers to build, maintain and productionise quantitative trading frameworks and strategies, develop tooling and ML pipelines, improve engineering standards, and deliver robust production solutions for systematic trading.

Build and own cloud infrastructure and GPU compute environments for ML model training and deployment. Implement IaC, CI/CD, orchestration, containerisation, monitoring, security, and internal tooling to enable reproducible, scalable research-to-production ML workflows.