Top Python Jobs in London

Lead product direction and build agentic AI systems for autonomous merchandising optimisation: prototype multi-agent flows, take prototypes to production, define trust/governance, drive measurable experiment throughput and conversion uplift, and partner across engineering, data science, and brand teams.

Validate and benchmark ML models on Graphcore's software/hardware stack. Create automated benchmarking pipelines, run open-source models, design targeted tests for numerical precision, quantisation, attention, distributed execution, and debug performance and correctness issues across frameworks and environments.

Leads development of high-performance C++ software, real-time and distributed simulation systems, and complex software and hardware integrations. Architects scalable systems-of-systems solutions, establishes technical standards, mentors engineers, and leads projects with 10 or more contributors. Responsibilities include debugging, optimization, agile development, continuous integration, test-driven development, task decomposition, and collaboration across teams.

Deploys, integrates, maintains, and develops AI training factory components in isolated environments. Responsibilities include integrating tooling onto hardware, managing software updates and configuration across environments, ensuring platform reliability, coordinating with autonomy teams, troubleshooting distributed systems, and developing automation. The role requires cloud, Kubernetes, Linux networking, C++ or Python application support, and onsite availability in London.

Leads analytics strategy and execution for Wise’s Internal Audit function, managing 1–2 analysts while delivering audit analytics, automation, continuous testing, AI initiatives, and management-information dashboards. Partners with stakeholders across risk, finance, technology, operations, financial crime, analytics, and engineering. Ensures analytical quality, rigor, and impactful insights across global audit programs.

Design, build, test, and maintain scalable full-stack web applications and integrations using Java, Python, and React. Implement AI-enabled features, event-driven data pipelines, and marketing integrations (CDP/CRM/CMS). Improve code quality via AI-assisted tools, CI/CD, observability, and security/compliance best practices while collaborating with product, marketing, and partners.

Lead design, development, and delivery of risk, pricing, trade capture, and commodities operations software. Collaborate with trading, quant, sales, and middle office to produce secure, high-quality production code, provide technical guidance, and drive product and architecture decisions. Promote cross-team collaboration, firmwide engineering practices, and mentor engineers to deliver scalable solutions.

Build and maintain DevSecOps tooling for AWS cloud environments, including threat modeling, security guardrails, policy-as-code, vulnerability analysis, compliance reporting, and runtime security visibility. Develop automation for security findings and software supply chain controls, support audits and incident response, and provide remediation guidance to engineering teams. Collaborate with platform engineers, product squads, risk, and governance teams while using authorized AI-assisted development tools securely and validating generated outputs.

Support the evolution and adoption of LLM Suite, JPMC’s internal generative AI platform. Identify and prioritize AI use cases, research market trends, develop business cases, define roadmaps, and coordinate delivery with senior stakeholders, technology teams, and business lines. The role requires relationship management, analytical problem-solving, executive communication, risk mitigation, and influencing cross-functional teams without direct authority.

Develop and enhance high-performance portfolio construction and quantitative research technology. The role involves full software development lifecycle ownership, designing scalable systems, applying Python or Java expertise, collaborating with technologists and stakeholders, communicating development progress, and contributing to innovation and continuous improvement within a large financial-services engineering team.

Support People team with headcount and cost analysis, build dashboards, update hiring forecasts and workforce plans, run scenario modelling, automate reporting, and prepare executive-level presentations to inform strategic decisions.

Develop and deploy statistical, machine learning, mathematical, and optimization models for Prime Finance. Responsibilities include forecasting borrow rates and demand, optimizing pricing and inventory allocation, researching alpha signals and hedging strategies, building analytics infrastructure, managing model risk, and communicating results to trading, technology, risk, and senior stakeholders. The role also mentors junior researchers and documents methodologies.

Design, implement, and deploy customer-specific video platform integrations and infrastructure. Ingest and transform large data sets, build automation and CI/CD pipelines, ensure production readiness, and provide third-line support. Collaborate with architects, PMs, global engineering, and customers throughout solution lifecycle, emphasizing scalability, reliability, and operational sustainability.

Own the global marketing measurement framework spanning attribution, experimentation, and Marketing Mix Models. Lead two analysts, develop the measurement product roadmap, build scalable attribution features using SQL, Python, and dbt, and generate insights to optimize marketing channels and spend. Partner with marketing, data science, engineering, and finance teams while serving as the subject matter expert on advertising effectiveness and communicating recommendations to technical and non-technical stakeholders.

Analyze paid social audiences and platform performance to identify bidding, budget, and testing opportunities. Design experiments, validate measurement signals, maintain dbt data pipelines, and build reliable BI dashboards. Develop analytical frameworks for budget optimization, investigate anomalies, and communicate insights, risks, and trade-offs to marketing stakeholders. Collaborate with platform, data science, marketing science, and analytics engineering teams while applying attribution, unit economics, incrementality, and marketing measurement expertise.

Lead end-to-end growth and marketing analytics across regions, channels, products, and customer segments. Use SQL, Python, AI, and automation to identify performance drivers, opportunities, risks, and trade-offs. Build dashboards, analytical frameworks, automated reporting, and scalable workflows. Partner with senior marketing and product stakeholders, translate ambiguous questions into actionable recommendations, and connect insights to measurable business impact.

Lead Wise’s Growth analytics team, managing three analysts and influencing company and customer decisions through data. Responsibilities include analyzing growth drivers, developing repeatable performance frameworks, partnering with data science teams on customer models, curating datasets, defining metrics, statistical modeling, deep-dive analysis, stakeholder management, and communicating insights through data visualization and storytelling.

Analyze Wise Platform pricing, costs, and profitability to identify pricing improvements and growth opportunities. Investigate complex cost data, improve data quality and allocation methodologies, explain product economics, monitor financial performance, and support pricing model enhancements. The role requires advanced SQL, visualization, dbt data modeling, stakeholder influence, and collaboration across analytics, engineering, and business teams.

Generate actionable growth and financial insights through dataset curation, metric development, statistical modeling, and deep-dive analysis. Analyze company and regional growth drivers, customer segments and cohorts, and the financial impact of marketing and product initiatives. Build data visualizations and communicate findings to influence business decisions, while managing stakeholders and organizing work independently.

Leads the design, development, and support of enterprise data platforms and pipelines. Ingests, cleanses, models, and documents data from diverse sources into governed Kimball datasets for BI, machine learning, and AI. Oversees data engineers, ensures pipeline reliability and quality, applies DevOps and CI/CD practices, performs data analysis, and collaborates with stakeholders on requirements, governance, GDPR compliance, and continuous process improvement.

Drive analytics for financial crime screening products, balancing risk mitigation with a smooth customer experience. Responsibilities include defining and tracking metrics, building data pipelines, preparing reports and visualizations, conducting discovery analysis, identifying control and customer-experience improvements, and communicating actionable insights to product, engineering, and operations stakeholders.

Own end-to-end regulatory reporting datasets across multiple jurisdictions, including regulatory data mapping, automated pipelines, visualizations, data quality controls, monitoring, and discrepancy resolution. Collaborate with finance, compliance, regulatory, product, and analytics teams to support licensing, audits, partnerships, and controlled growth. Use SQL, dbt, Snowflake, Airflow, visualization tools, and AI capabilities to deliver accurate, scalable reporting infrastructure.

Lead pricing analytics for Wise Platform by investigating cost data, improving data quality and allocation methodologies, monitoring financial performance, and identifying profitability and growth opportunities. The role requires building complex SQL data sources, developing reusable dbt models, explaining product economics, influencing pricing strategies, and partnering with analytics, engineering, and business teams.

Lead marketing analytics infrastructure that explains growth drivers, automates insight generation, and turns complex performance data into actionable narratives. Build and maintain analytical tools, including Lightdash reports, Streamlit apps, and AI-enabled automation. Identify opportunities in marketing financial processes, ensure data quality, develop growth frameworks, and partner with marketing, regional, product, and analytics teams to translate findings into strategic execution.

Sell and grow JPMorgan's electronic Rates execution franchise across EMEA by managing client relationships, analyzing flow and platform performance, leading commercial discussions, translating client requirements to technology teams, and coordinating with trading, quant, and venue partners to drive electronic adoption and regulatory/compliance responses.