Top Python Jobs in London

Lead the creation and growth of Genomics England’s SRE capability. Build and manage an initial team, identify high-value reliability improvements, establish engineering standards and tooling, reduce operational toil, and embed SRE practices across product squads. The role provides hands-on technical leadership across cloud and on-premise platforms, CI/CD, infrastructure as code, monitoring, resilience, and operational strategy while coaching teams and influencing engineering direction.

Leads the strategy and architecture for scalable search and AI retrieval systems. Responsibilities include selecting search technologies, designing keyword, vector, hybrid, and graph retrieval, developing knowledge graphs, building LLM-powered enrichment and recommendation pipelines, and architecting GCP data infrastructure. The role requires strong Python skills, production search experience, cloud-native expertise, and technical leadership.

Build, deploy, operate, and maintain scalable Palantir infrastructure and services for UK government customers. Responsibilities include monitoring, configuration management, product deployments, migrations, troubleshooting production issues, participating in on-call support, improving reliability, and automating manual workflows. The role also develops infrastructure solutions within Foundry and Apollo while collaborating with forward-deployed and product teams.

Analyze Sportsbook product performance through testing, reporting, ad hoc queries, and data-driven insights. Partner with product stakeholders, Analysts, and Data Scientists to optimize user experiences, track metrics, solve business problems, and support product development. Present findings to senior stakeholders and serve as a trusted source of analytical intelligence.

Supports test planning and execution for audio hardware and software products, including functional, performance, and regression testing. The role identifies defects, documents test results, communicates findings with engineering and product teams, and contributes to quality improvements in an audio manufacturing environment.

Produce analytical evidence for AI product decisions by scoping questions, designing experiments, building prototypes, analyzing guardrail performance, benchmarking metrics, and recommending actions to product managers. Work includes evaluating AI safety controls, measuring accuracy, latency and cost, prototyping workflows, and reporting results. The role develops expertise in AI security, guardrails, agent systems, and experimental design while providing a path toward product management.

The Full-Stack Engineer will enhance backend functionality, collaborate with teams, and maintain platform performance and security, requiring expertise in Python.

Build and optimize scalable ETL/ELT pipelines, Spark jobs, Airflow DAGs, and dbt transformations. Design Lakehouse architectures using S3, Iceberg, and Delta Lake; develop reusable platform frameworks, CI/CD pipelines, data contracts, observability, and data quality controls. The role also supports streaming technologies, cloud data warehouses, dimensional modeling, schema evolution, and AI-enabled engineering improvements.

Develop and apply experimental and computational methods for in situ cell lineage tracing using spatial single-cell multiomics. Generate and analyze large sequencing datasets, optimize laboratory and computational workflows, maintain reproducible records, publish findings, collaborate with researchers, present results, contribute to grants, and co-supervise students. The role combines molecular biology, experimental genomics, computational analysis, tissue-based methods, and method development.

Conduct postdoctoral research developing high-throughput environmental exposure screening platforms using in vitro or in vivo models. Design molecular and phenotypic readouts, generate and analyze high-dimensional sequencing and screening datasets, and apply R or Python. Responsibilities include method development, reproducible laboratory work, publications, grant contributions, presentations, collaboration, student co-supervision, and laboratory compliance. In vivo applicants need animal-work experience and a UK Home Office personal licence or readiness to obtain one.

Designs, builds, and operates scalable machine learning platforms, infrastructure, deployment frameworks, and backend services for search, recommendations, and personalization. Responsibilities include CI/CD, batch and real-time inference, observability, infrastructure automation, distributed compute optimization, incident management, architecture, and technical mentoring. The role partners with data scientists, software engineers, data engineers, and product managers to deliver reliable cloud-native ML systems at scale.

Leads product analytics for ASOS, owning KPIs, customer funnel analysis, experimentation, A/B testing, dashboards, and data-driven product strategy. Partners with Product Managers and senior stakeholders to identify growth opportunities, improve conversion, engagement, and retention, and shape roadmaps. The role also mentors junior analysts and promotes rigorous, insight-led decision-making across product teams.

Ten-week Debt Capital Markets internship supporting desk analytics, market analysis, pricing, risk, financing strategy, and transaction execution. Interns will gain exposure to credit markets, capital structures, bond financing, and global financial markets while presenting findings and collaborating with senior leaders. The program includes technical training, mentorship, workshops, and speaker sessions. Candidates should demonstrate quantitative ability, financial markets interest, technical proficiency, communication, leadership, teamwork, and initiative.

Leads the design, development, testing, integration, and optimization of scalable data-processing and persistence components. Establishes engineering and operational standards, ensures pipeline performance and compliance, troubleshoots systems, supports proposals, and collaborates with architects, operations, security teams, customers, and managers. Coaches and develops engineers while overseeing code quality, data models, testing, deployment readiness, and technical delivery.

Own marketing analytics across the inbound funnel, attribution, channel and campaign performance, CAC, LTV, and revenue contribution. Build dbt models and semantic-layer metrics using BigQuery and marketing platforms, maintain web and lead-data instrumentation, ensure data quality and GDPR compliance, and provide actionable insights to marketing, sales, and leadership.

Leads advanced data science projects and specialized modeling for media effectiveness and marketing analytics. Translates complex analytical requirements into deployable solutions, contributes hands-on to machine learning and statistical modeling, develops analytical tools and dashboards, and applies AI and generative AI. Manages projects from conception through delivery, communicates technical concepts to stakeholders, and provides technical leadership across analytics, media, and data teams.

Data science intern working on real customer projects involving data wrangling, analysis, predictive modeling, visualization, and product insights. The role uses Python, SQL, Looker, and spreadsheets to transform raw data into customer stories and support data-driven product decisions. Interns collaborate with Data teams, learn commercial and product analytics, and complete a full-time 12-week hybrid internship in London.

Assesses and prices innovative reinsurance risks involving climate change, nature loss, health, conflict, migration, and other systemic risks. The role evaluates exposures, structures, expected losses, catastrophe models, assumptions, and pricing methodologies. It advises senior underwriters, supports parametric and non-traditional product development, prepares market insights, and collaborates across actuarial, modelling, analytics, sustainability, brokers, governments, NGOs, and development organizations.

Build and evolve Azure-based data platform capabilities supporting data science, machine learning, and analytics at scale. Develop high-performance pipelines with Python, Scala, Spark, and Databricks; improve reliability, observability, data quality, and cost efficiency; create reusable engineering tools and patterns; contribute to architecture and technical standards; and mentor engineers across teams.

Build and scale governed data products, pipelines, analytical models, semantic layers, APIs, and AI-enabled interfaces. Establish standards for data modeling, orchestration, testing, observability, CI/CD, security, and lifecycle management. Partner with stakeholders to define data contracts and product roadmaps, deliver solutions end to end, improve analytics governance, and mentor colleagues. The role requires strong data and analytics engineering expertise, product judgment, and practical experience directing AI coding agents.

Build the AI foundation for Home Assistant, including conversation APIs, LLM integrations, typed tool layers, agents, MCP connectivity, memory, and AI-powered workflows. Develop reliable, private, local-first features and integrate local or cloud models. Review code, collaborate with the open-source community, investigate issues, guide architectural decisions, and contribute to a remote asynchronous engineering culture.

Build and deploy production AI and machine learning capabilities across Anaplan’s platform. Responsibilities include developing GenAI features, integrating and monitoring LLMs, implementing RAG and agentic systems, designing vector and knowledge graph retrieval layers, engineering batch and streaming data pipelines, and creating evaluation frameworks. The role combines advanced data engineering, MLOps, LLMOps, model serving, prompt engineering, and enterprise planning analytics.

The Senior Marketing Data Scientist will measure and optimize marketing performance using marketing mix modeling, attribution, customer lifetime value analysis, experimentation, and causal inference. Responsibilities include building scalable data pipelines, automating model deployment and monitoring, creating dashboards, analyzing campaigns, and communicating insights to executives. The role requires strong Python and SQL skills, experience with open-source marketing mix models, marketing analytics expertise, and the ability to lead projects independently.

Leads the engineering organization responsible for modeling, rendering, simulation, distributed computing, and quality. Owns platform roadmap execution, manages engineering managers, accelerates AI-assisted software development, improves delivery and testing processes, and balances zero-to-one product development with ongoing releases. Partners with Product and represents platform engineering to company leadership. Requires deep technical credibility and a proven record of organizational transformation, product delivery, and engineering leadership.

Manage and optimize production Kubernetes clusters on GKE using Terraform, build secure and scalable cloud infrastructure, and develop golden paths and self-service automation for developers. The role supports cloud compliance standards, provides technical expertise on GCP and Kubernetes, maintains infrastructure documentation and solutions, and participates in an on-call rotation. Experience with AWS, CDK, Datadog, and cloud security practices is advantageous.