Top Python Jobs in London

Leads Ipsen’s statistical innovation strategy across R&D, including innovative trial design, simulation, advanced modeling, predictive analytics, digital twins, virtual controls, and data mining. Manages a specialist quantitative team, establishes methodological standards, supports regulatory and portfolio decisions, and partners with biostatistics, clinical development, data science, and other cross-functional groups. Develops talent, oversees reproducible and submission-ready methods, and builds external scientific networks.

Build and productionize ML and LLM-powered recommendation features serving millions of users. Own end-to-end systems spanning data pipelines, feature engineering, model training, real-time serving, APIs, monitoring, A/B testing, and distributed infrastructure. Collaborate with Product, Design, Engineering, and Platform teams while optimizing performance, cost, latency, reliability, and user experience.

Build and optimize scalable full-stack web applications using React, Python, JavaScript, and TypeScript. Deploy cloud-native solutions, preferably on Azure, integrate APIs, microservices, LLM-based services, and agentic AI systems, and support containerized environments and CI/CD pipelines. The role also emphasizes high-throughput applications, front-end performance, observability, and reliable deployments while collaborating with backend, cloud, and AI engineering teams.

Develop, implement, and maintain pricing and calibration models and curve construction frameworks for inflation derivatives (swaps, caps/floors, options). Collaborate with traders, structurers, risk and model validation to ensure robust, performant production analytics. Implement and test models in production libraries, monitor performance, produce documentation, and stay current with market practice and regulatory expectations.

Analyzes marketing, sales, customer experience, e-commerce, retail, and campaign performance data. Builds scalable BigQuery and Looker Studio dashboards, defines data models and commercial KPIs, measures campaign uplift and halo effects, analyzes customer journeys and content performance, and translates findings into actionable recommendations for cross-functional stakeholders.

Analyze marketing, sales, customer experience, e-commerce, retail, and promotional performance. Build and maintain scalable BigQuery-backed Looker Studio dashboards, define data models and commercial KPIs, measure campaign uplift and halo effects, analyze customer journeys and content performance, and translate findings into actionable recommendations for cross-functional stakeholders.

Develop and evaluate LLM applications, agentic systems, and retrieval pipelines for maritime data. Partner with Product Managers to prototype AI solutions, define evaluation criteria, design architectures, and transition successful work into production. Build embedding and retrieval pipelines, evaluation suites, guardrails, observability, and responsible AI practices on Azure and Databricks. Communicate findings, contribute to shared tooling, and guide adoption of effective AI technologies.

Consolidate and modernize PALU and CIMS data and deployment systems across Databricks, AWS, GitLab CI/CD, PostgreSQL, and dbt. Responsibilities include assessing Databricks, building data pipelines and models, configuring CI/CD, optimizing AWS costs, implementing containers and infrastructure as code, managing security and backups, monitoring systems, resolving maintenance issues, documenting configurations, and training MCD staff for independent system operation.

Build and maintain secure, auditable internal automations for finance, IT, People, and delivery workflows. Develop API integrations with Microsoft Graph, Slack, Atlassian, banking, HR, and identity systems; manage authentication, deployment, observability, and audit controls. Apply LLMs and agentic patterns selectively with human approval gates, while meeting SOX, ISO 27001, SOC 2, EU AI Act, and data protection requirements. Partner with process owners, Finance, Security, and Legal to simplify workflows and operate reliable production systems.

Build, train, optimize, and integrate machine learning and large language model systems for real-time games and interactive experiences. Own projects across the ML pipeline from data preparation and experimentation through production deployment. Collaborate with engineers, artists, writers, and designers to create compelling AI-powered products, with emphasis on performance, latency, efficiency, and creative applications.

Build and own full-stack internal tooling and creator-facing workflows for AI-powered games. Translate the needs of designers, artists, writers, engineers, and external partners into intuitive, scalable applications and narrative systems. Collaborate across disciplines, iterate based on developer feedback, and write performant, maintainable production code with significant end-to-end ownership.

Two-year graduate scheme training candidates as applied macroeconomists through rotations across four teams and internal training. Responsibilities require conducting macroeconomic research, learning quickly, writing clearly, and meeting tight deadlines. Successful trainees may receive postgraduate study sponsorship and transition into permanent roles after completing the scheme.

Designs and leads Datadog customer implementations from requirements gathering through architecture, automation, deployment, and launch. Guides onboarding and co-development sessions, resolves technical roadblocks, develops deployment templates, manages implementation projects, and collaborates with Customer Success, Technical Account Management, and Sales. Requires cloud, DevOps monitoring, infrastructure-as-code, CI/CD, configuration management, and programming experience, plus at least five years as an architect or consultant. Travel up to 30% is required.

Develop physics-based and data-driven vehicle dynamics models, integrate them into software and simulation workflows, and validate performance against experimental and on-road data. The role includes mathematical modelling, numerical analysis, software optimisation, experimental test planning, performance analysis, and cross-functional collaboration with robotics, simulation, and product teams supporting autonomous driving systems.

Monitor and analyze security alerts, investigate and respond to incidents across Windows, macOS, and Linux, perform malware and forensic analysis, remotely remediate threats, and improve detection and response processes. Serve as a technical escalation point, mentor junior analysts, oversee quality assurance, manage internal programs or teams, communicate findings to customers, and contribute thought leadership through public speaking and content.

Leads and develops a global Enterprise Architect team supporting sales and strategic customer engagements. Acts as an executive sponsor, presents architecture strategies to C-level stakeholders, removes technical blockers, and guides enterprise modernization, data, cloud, integration, scalability, and Agentic AI initiatives. Partners across sales, product, engineering, security, and customer teams while overseeing architecture readiness, reusable assets, thought leadership, and ecosystem enablement.

Supports AWS-based SaaS environments by monitoring infrastructure, troubleshooting incidents, deploying and maintaining cloud services, performing health checks, following runbooks, participating in on-call rotations, and communicating with customers and internal teams. The role also documents operational procedures, collaborates on reliability improvements, and uses AI tools to enhance engineering workflows.

Provides client-facing consulting on defensible applications of analytics, machine learning, generative AI, and technology-assisted review in eDiscovery and legal data workflows. Designs, configures, validates, and explains AI-enabled review solutions across platforms such as Relativity and Reveal AI. Advises on workflow strategy, privilege, quality control, statistical validation, and defensibility while managing projects, collaborating cross-functionally, mentoring colleagues, and supporting demonstrations and business development.

Build and maintain dbt-based ELT pipelines and scalable data models in Snowflake or similar cloud warehouses. Ensure data quality through testing, monitoring, documentation, lineage, and CI/CD practices. Optimize SQL queries and warehouse performance, develop Looker visualizations, and collaborate with data engineers, analysts, and business users. Champion modern data-stack adoption, with preferred experience in Python, semantic layers, Airflow, and software engineering practices for data.

Develop and maintain secure cloud-based applications and services primarily in AWS. Build APIs, integrations, databases, and data flows using Python, JavaScript, SQL, and PostgreSQL. Apply testing, secure development, Git, Docker, and DevOps practices within agile multidisciplinary teams. Translate business needs into technical solutions, collaborate with stakeholders, support live services, contribute to technical standards, and mentor developers. Current SC security clearance is required before starting.

Lead product analytics for Wise Business: define and track KPIs/OKRs, build data logging and automated pipelines, run deep-dive analyses, quantify feature impact for prioritization, and translate findings into clear recommendations for product and leadership.

Develop marketing budget allocation models, Early LTV metrics, performance diagnostic frameworks, and analytical tools. Analyze products, channels, campaigns, cohorts, attribution, and marketing economics using SQL, experimentation, BI tools, and spreadsheets. Support AI-based analytics development and unified BI metrics while translating findings into business rules and recommendations.

Lead complex data analytics initiatives for top financial institutions, utilizing predictive modeling and creating dashboards. Support innovation in AI and machine learning.

Design, implement, and improve security controls across Kubernetes, cloud-native, and datacentre infrastructure. Secure networks and firewalls, integrate DevSecOps controls into CI/CD, lead vulnerability management, build detection/response capabilities, automate security workflows, and support incident response and threat hunting for GPU-accelerated and AI/ML platforms.

Leads business insights for global eCommerce by analyzing commercial performance across merchandising, pricing, marketing, CRM, content, supply chain, and customer behavior. Identifies anomalies, root causes, risks, and opportunities through hypothesis-led analysis, then delivers prioritized recommendations and executive-ready data stories. Partners with cross-functional and market teams to support performance reviews, planning, and commercial decision-making.