Top Python Jobs in London

Deliver catastrophe modeling, exposure management, and portfolio analytics across Markel International. Support underwriting decisions through pre-underwriting analysis, risk reporting, aggregation management, and ad hoc insights. Build relationships with underwriters and senior stakeholders, present analytical findings, collaborate with global teams and model vendors, and contribute to portfolio analytics projects and regulatory reporting for Lloyd’s and the PRA.

Analyzes and monitors hedge fund risk, performance, and data integrity for the Schroder GAIA liquid alternatives platform. Maintains daily risk and performance data processes, develops reports and analytical solutions, interprets investment data using Snowflake, Python, and Alteryx, and supports risk models and systems. The role collaborates with fund managers, research teams, product teams, and external providers while developing expertise in portfolio risk, performance attribution, and alternative investment strategies.

Develop and maintain embedded firmware for IoT smart home devices using constrained microcontrollers and real-time operating systems. Responsibilities include requirements analysis, firmware development, hardware debugging, board bring-up, testing, optimization, code reviews, bug resolution, and field deployment. The engineer will collaborate with hardware, platform, app, and customer-facing teams while working with communication protocols, IoT security, networking, and connected-device technologies.

Develop and enhance software, data pipelines, automated controls, reporting, and analytical tools supporting the full energy trade lifecycle. The role focuses initially on settlements, commercial finance, P&L, position reporting, reconciliation, and exception management across power, gas, carbon, and battery assets. Responsibilities include integrating Aligne, Microsoft Fabric, and internal systems; replacing manual processes with scalable applications; and collaborating with settlements, finance, trading, quantitative analytics, IT, and data architecture teams.

Build and own full-stack features for a cloud platform supporting autonomous drone operations. Responsibilities include developing React and FastAPI applications, APIs, data pipelines, storage systems, mission-planning interfaces, operational views, and data review workflows. The role requires scaling systems handling imagery, telemetry, and flight records, while improving testing, observability, CI/CD, architecture, and engineering practices. Collaboration spans flight operations, autonomy, inspection, asset, and customer teams.

Lead the architecture and technical direction of OQC’s hybrid compute platform, connecting CPUs, GPUs, simulators, and QPUs. Design stable interfaces, orchestration, capability matching, fallback mechanisms, policy enforcement, and backend adapters. Establish standards for reliability, security, testing, observability, and extensibility while remaining hands-on with implementation. Coordinate technical contributors across product, engineering, commercial, and leadership teams, and lead integrations with infrastructure, Databricks, QPU systems, and customer environments.

Lead the development, testing, debugging, and technical design of scalable backend systems, integrations, and cloud applications. Establish engineering standards through code reviews, automated testing, DevSecOps, observability, incident management, and operational excellence. Partner with architects, product managers, business stakeholders, and external partners to deliver commercial planning solutions. Mentor engineers, provide technical guidance, and evaluate emerging technologies and AI-enabled development practices.

Designs, implements, administers, and improves Cisco ISE and NAC services across wired, wireless, and remote networks. Manages AAA, 802.1X, device profiling, posture assessment, segmentation, guest access, and Zero Trust policies. Troubleshoots complex access issues, maintains platform resilience and documentation, leads testing and upgrades, and delivers roadmap initiatives. Collaborates with network, security, infrastructure, engineering, product, and business teams while supporting both operational services and project delivery.

Delivers reporting, dashboards, and ad hoc analysis while supporting data science activities across racing and sports. Responsibilities include SQL-based data work, production support for Python scripts and data platforms, model testing and validation, data science project overflow, and stakeholder collaboration. The role requires flexibility between structured analyst work and exploratory data science problem-solving.

Support building and maintaining data pipelines, onboard and transform partner data, monitor reliability, validate data quality, automate processes, and document pipeline logic to ensure trustworthy datasets for the business.

Design and deliver scalable data solutions on Microsoft Azure. Collaborate with engineers, analysts, architects, and product teams; support data, telemetry, and operational understanding; develop proof of concepts; and build reliable, tested, maintainable solutions using CI/CD. Contribute to engineering standards, agile delivery, data modeling, performance and cost optimization, and adoption of emerging data technologies.

Participate in a 24-month rotational trading analyst program supporting trade execution, transaction processing, reconciliations, reporting, controls, client servicing, and process improvement. Monitor pricing, liquidity, and execution details; investigate exceptions; analyze trends and performance; and gain exposure to market structure, trading workflows, and risk management. The role develops quantitative, analytical, data, and financial services skills through project work, mentorship, and cross-functional collaboration.

Design, deploy, and operate highly available, multi-region SaaS infrastructure on AWS. Build Kubernetes-based platform tooling, automate deployments and operational processes, improve reliability and security, conduct scale and chaos testing, and participate in 24x7 incident response. Collaborate with software engineering teams to optimize performance, resilience, and operational excellence across a microservice platform.

Build and deploy production-grade AI solutions across data ingestion, feature engineering, model training, evaluation, and deployment. Develop LLM integrations, agentic workflows, RAG architectures, dashboards, backend APIs, and prompt-engineering solutions. Collaborate with fixed-income business users, engineering, data engineering, and application support teams. Maintain production applications, write tested and documented code, and evaluate emerging AI/ML technologies.

Build and operate market-specific integrations for a European financial technology platform. Responsibilities include data ingestion and transformation, API integrations with payment and communications providers, validation, reconciliation, idempotency, replay mechanisms, localization, defect resolution, client onboarding, and roadmap influence. The role serves as the primary technical authority for enterprise financial institution integrations, develops reusable integration patterns, engages with clients and partners, and mentors mid-level engineers.

Lead technical customer onboarding, integrations, training, observability strategy, troubleshooting, and success planning. Advise customers from DevOps teams to executives, conduct QBRs, demonstrate ROI, advocate for product improvements, and collaborate with Sales on renewals and expansion. The role requires strong AWS, Kubernetes, Docker, Linux, observability, infrastructure-as-code, and communication expertise.

Build, maintain, and evolve RHEL and Ubuntu platforms supporting quantitative research. Responsibilities include OS image creation, provisioning and lifecycle management, Ansible automation, Linux security hardening, vulnerability response, kernel and package remediation, observability, telemetry, APIs, databases, and agentic frameworks for autonomous operations. The role requires strong Linux expertise, programming ability, infrastructure automation skills, and collaboration.

Build and operate platform services, APIs, workflows, and data models for storage infrastructure. Automate capacity, tenant, quota, access, and data lifecycle processes with safe, auditable, idempotent changes. Develop tests, observability, and stable service contracts while troubleshooting production systems, responding to incidents, and participating in on-call rotation. Collaborate with users and partner teams to convert operational challenges into reliable engineering solutions.

Build and maintain consumer-credit risk, value, revenue, profit, and customer lifetime value models. Translate ambiguous credit questions into practical analyses and classification or regression solutions using Python and statistical judgment. Partner with Credit Strategy, Product, and Engineering to prioritize work, productionize models, explain technical decisions, and drive alignment. This hands-on individual-contributor role offers mid- and senior-level scope in a collaborative hybrid environment.

Analyze transaction-enrichment data using Python and SQL, identify failure patterns, form hypotheses, and prototype solutions. Design evaluations, including LLM-as-judge methods, to assess accuracy, cost, and coverage trade-offs. Translate findings into product recommendations and implementation guidance while collaborating with Product and Engineering. The role requires practical experimentation, LLM API usage, data-quality analysis, and clear communication with technical and nontechnical stakeholders.

Analyze pricing, loan funnel, and credit optimization opportunities within Lendable’s UK Loans team. Responsibilities include researching pricing strategy improvements, developing analytical models, collaborating with credit and product teams, working with large datasets, communicating findings to stakeholders, and gradually taking ownership of models. The role requires Python, SQL, statistical and machine learning knowledge, strong numerical ability, and effective teamwork.

Design, build, and deploy production-grade ML systems and reusable infrastructure. Collaborate with cross-functional teams, lead technical scoping and architecture, define deployment standards, and advise clients on ML feasibility and delivery.

Researches and applies advanced machine learning, NLP, and information retrieval techniques to improve Microsoft 365 Copilot Chat and Search quality. Responsibilities include developing vector retrieval and embedding solutions, analyzing user journeys and model behavior, evaluating search relevance, adapting large language models, and partnering with engineering and product teams. The role also involves building scalable evaluation tools, mining data for opportunities, and contributing to internal or published research.

Maintain, deploy, troubleshoot, and modernize large-scale production Linux infrastructure. Build automation, improve reliability and operational efficiency, support trading system applications, and troubleshoot networking, performance, and kernel issues. Participate in global on-call rotations, change and incident management, documentation, infrastructure integration, and technical review forums while collaborating with engineering, development, operations, and project teams.

Analyze end-to-end operational processes using interviews, documentation, system data, SQL, Python, and process-mining insights. Identify automation, analytics, ML, and AI opportunities; quantify impact and feasibility; map as-is and to-be workflows; define KPIs and delivery-ready use cases; support prioritization, stakeholder communication, adoption, and value realization. The role works upstream of engineering to improve digitalization pipeline quality and ensure initiatives address real operational needs.