Top Python Jobs in London

Leads strategic market-modeling projects from discovery through implementation for live insurance pricing. Develops and improves statistical and machine learning models, ensures governance and fair customer outcomes, and collaborates with pricing, underwriting, data, and ML engineering teams. The role owns complex analytical problems, supports model deployment, mentors junior colleagues, and communicates technical recommendations to varied audiences.

Lead end-to-end delivery of production-grade machine learning and AI solutions, from discovery through deployment and optimization. Partner with stakeholders to identify commercially valuable use cases, design scalable predictive applications, establish data science and MLOps best practices, and collaborate with engineering, platform, and product teams. Provide technical leadership, mentor practitioners, support agile delivery, and help advance the organization’s AI capabilities.

Lead end-to-end machine learning and AI solutions from discovery through production and optimization. Partner with stakeholders to identify commercially valuable use cases, design scalable predictive analytics applications, and establish best practices across data science, MLOps, experimentation, and software engineering. Collaborate with data engineering, platform, and product teams while providing technical leadership, mentoring, and guidance on production-grade AI products.

Lead strategic market-modeling projects from discovery through live pricing implementation. Develop and improve advanced statistical and machine-learning models, ensure model governance and fair customer outcomes, and collaborate with pricing, underwriting, data, and ML engineering teams. The role also involves autonomous project management, coaching junior colleagues, communicating complex analysis clearly, and identifying opportunities to improve model accuracy, competitiveness, profitability, and growth.

Leads the platform engineering function, owning strategy, internal developer platforms, self-service tooling, CI/CD, infrastructure, observability, reliability, and data operations. Builds and mentors platform and data operations teams while remaining hands-on with coding, design reviews, and prototyping. Establishes reliable data pipelines, security and cost controls, developer experience metrics, incident practices, and technical roadmaps aligned with business goals.

Leads analytics workstreams for market strategy consulting engagements, including market sizing, opportunity assessment, commercial modeling, scenario analysis, and quality assurance. Translates ambiguous client needs into analytical approaches, presents actionable insights, contributes to proposals, and manages client relationships. Mentors junior analysts, coordinates stakeholders, and delivers multiple projects across teams.

Build and operate backend services and streaming data pipelines that ingest sensor, rail, and waterway data into Kpler’s commodities intelligence platform. Responsibilities include developing Python and FastAPI services, maintaining Kafka and Airflow pipelines, validating time-series data, deploying cloud services, monitoring systems, improving CI/CD, supporting customer-facing applications, and participating in on-call operations.

Build and own high-performance distributed data systems supporting multimodal AI workloads. Responsibilities include designing, deploying, monitoring, and scaling storage, indexing, querying, processing, protocols, and APIs. The role requires production service ownership, sound architectural judgment, performance optimization, reliability engineering, and mentoring through code reviews, pairing, and knowledge sharing.

Own the UK loans origination funnel and onboarding journey, improving conversion across web and app experiences. Responsibilities include product strategy, roadmap definition, engineering delivery, hypothesis-driven testing, data analysis using Python or SQL, AI-enabled workflow automation, stakeholder collaboration, compliance-aware innovation, and third-party partnerships. The role requires independent product ownership, prioritization, communication, and effective collaboration across Engineering, Credit, Data Science, Finance, Design, Growth, and Operations.

Leads biostatistical support for clinical development, including trial design, protocol development, statistical analysis plans, regulatory submissions, data interpretation, and health authority interactions. Manages multiple studies, ensures quality and standards compliance, contributes to strategic drug development decisions, presents analyses, collaborates cross-functionally, and mentors team members.

Graduate Software Engineer working across backend engineering and market connectivity teams. Responsibilities include developing and enhancing software, building features with stakeholders, contributing to design, development, integration, automated testing, and maintenance, and collaborating with quantitative, product, infrastructure, and support teams to deliver trading solutions.

Develop and deploy data science, machine learning, and AI solutions for secure government and intelligence environments. Responsibilities include predictive modelling, NLP, graph analytics, data integration, anomaly detection, model validation, dashboards, and production deployment. The role collaborates with engineering and operational teams to deliver automated insights and decision-support capabilities, while contributing to AI/ML strategy and technical roadmaps.

Designs, implements, operates, and maintains Marex’s global network infrastructure. Responsibilities include network consultancy, operational support, security design, troubleshooting, vendor management, cloud networking, automation, infrastructure as code, and reporting. The role supports WAN, campus LAN, firewalls, exchange connectivity, and low-latency networks while ensuring regulatory compliance and operational resilience.

Nine-week Business Analyst internship in LSEG’s Markets division, exposing students to capital markets, post-trade, risk, financial data, and technology platforms. Interns will analyze large datasets, use Python, SQL, Tableau, or Power BI, draw conclusions, propose solutions, and collaborate across teams. Applicants should demonstrate financial-markets interest, strategic thinking, adaptability, resilience, and communication skills. The hybrid role is based in London and includes in-person assessment stages.

Build and deploy practical AI tools, prototypes, applications, APIs, agentic workflows, and shared platform capabilities. Partner with business and engineering teams to drive AI adoption, improve solution performance and cost, and establish responsible AI governance. The role also involves evaluating emerging AI technologies, creating reusable patterns, mentoring colleagues, and mitigating AI risks across a regulated, multi-product organization.

Build end-to-end data, analytics, machine learning, generative AI, and agent-based solutions. Develop predictive models, conduct experiments, analyze trends, create insights, and support governed, secure, scalable data platforms. Collaborate in agile teams while applying data management, privacy, risk controls, and compliance practices. The program includes mentorship and training for students pursuing quantitative or technical degrees.

Provides deep technical sales support for Red Hat Lightwell, demonstrating trusted software supply chain solutions in customer build environments. Leads technical discussions with developers, platform engineers, security teams, and executives; configures repositories and pipelines; supports proofs of concept; advises on artifact signing, SBOMs, attestation, dependency management, and policy enforcement. Collaborates with engineering, sales, consulting, partners, and customers while delivering enablement, advocacy, and market feedback.

Leads the design, delivery, and support of Power BI and cloud-based business intelligence solutions for internal and external clients. Responsibilities include requirements gathering, stakeholder workshops, data and semantic modeling, dashboard and KPI development, reporting governance, quality assurance, client presentations, and delivery of concurrent reporting workstreams. The role also provides technical leadership, consultancy, documentation, and continuous improvement across reporting and analytics projects.

Builds and operates security controls, tooling, detection content, and automation across cloud and corporate environments. Responsibilities include SIEM/SOAR administration, log onboarding, endpoint security, cloud configuration and hardening, identity and access controls, Kubernetes security, secrets management, vulnerability remediation, incident investigation, audit support, and technical documentation. The role provides remediation guidance, improves detection quality, supports resilience exercises, and maintains auditable, version-controlled security configurations in a regulated healthcare environment.

Leads a specialist analytics team delivering reliable data, management information, reporting, and business insights for an unsecured lending function. Responsibilities include developing data sources and marts, automating reporting, improving data governance and regulatory controls, translating complex analysis for senior stakeholders, driving change, and coaching high-performing analysts. Requires strong SQL, SAS, Python, Power BI, Excel Power Pivot, and VBA expertise, plus consumer lending or credit risk experience.

Supports audience research, Answer Engine Optimisation audits, AI output evaluation, synthetic testing, structured data mapping, metric tracking, dashboards, scorecards, and client reporting. The role combines experience strategy, analytics, research, and hands-on assessment of generative AI systems, including accuracy, brand alignment, latency, cost, and hallucination monitoring. Collaboration spans data engineering, creative, technology, and strategy teams.

Analyze, clean, validate, and reconcile data from multiple sources; write SQL; maintain databases; build dashboards, reports, and KPIs; investigate discrepancies and integration failures; support migrations and data pipelines; and provide UK/Europe clients with data-related support. The role also requires documenting incidents, explaining technical findings to non-technical stakeholders, monitoring processing jobs, and collaborating with Product, Engineering, and Program Management.

Turn data into product and business decisions through metric definition, experimentation, causal analysis, deep-dive research, and clear recommendations. Model reliable analytical data in dbt, build scalable dashboards and reporting, partner with data engineering, and influence leaders across Product, Finance, Growth, GTM, and Customer Success. The role also helps establish data-team standards, tooling, and operating practices in an AI-first environment.

Own customer implementations from solution design through deployment and adoption. Build proofs of concept, integrations, custom workflows, data pipelines, and production-quality code using APIs and webhooks. Lead technical workshops, document solutions, troubleshoot live customer systems, provide on-call support, and convert recurring customer needs into reusable product improvements. The role is embedded with major internet platforms and requires strong engineering skills, customer ownership, initiative, and comfort with ambiguity.

Own database performance, scalability, availability, disaster recovery, and cost across a production SQL Server estate on Azure. Optimize queries, indexes, execution plans, and latency-critical card and ledger workloads; design horizontal scaling and HA/DR strategies; build diagnostic and automation tooling; lead incident response; and guide engineers on data access, ORM performance, migrations, and database architecture.