Top Python Jobs in London

Lead product analytics to drive growth by owning KPIs, designing and analysing A/B tests, surfacing high-impact opportunities across customer funnels, building dashboards and self-serve analytics, influencing product strategy with data, and mentoring junior analysts.

Work with Risk and Technology to identify, ingest and govern risk datasets into the firm's Data Platform. Document lineage, quality rules and ownership; automate validation and reconciliations; build and maintain Power BI reports and analytical models; translate risk business needs into data requirements and support risk-related technology projects and governance.

Work alongside salespeople and sales-traders to support institutional client engagement across asset classes. Learn how client inquiries are handled, service clients and issuers, attend internal training on finance and trading fundamentals, and develop analytical, communication, and relationship-building skills in a fast-paced environment.

The candidate will develop and maintain pricing and risk models, support trading activities, and enhance valuation tools, collaborating with various teams.

Build and deploy production-ready AI/ML systems across the full lifecycle, including agentic systems (RAG, prompt engineering), non-GenAI models (recommenders, forecasting), APIs/microservices, CI/CD and IaC, monitoring and guardrails, and cross-functional collaboration to ensure scalable, secure, and observable ML solutions.

The Senior Solutions Architect will lead initiatives on the FTSE Russell Index platform, ensuring operational efficiency, regulatory compliance, and platform modernization while collaborating with Product, Operations, and Engineering teams.

Lead and expand private markets research using FTSE Russell and Stepstone index data. Produce client-facing reports, white papers, webinars and presentations; apply quantitative methods and coding to analyze private equity, credit, real assets and integrate private markets into multi-asset portfolios. Collaborate with product, index, sales and marketing to support index strategies and client engagement.

Own and automate the GTM infrastructure: maintain CRM data quality, build enrichment/scoring workflows, detect buying signals, manage cold email deliverability, deploy AI agents and API integrations, run outbound campaigns and experiments, and partner with SDRs/AEs to scale revenue systems.

Design and build machine learning systems to detect fraud and policy violations, working with partners to translate requirements into effective models using LLMs and deep learning.

Analyze and investigate trading fraud cases, monitor trading activities to detect fraud, and improve fraud prevention processes.

Lead data architecture and AI-enabled transformation projects for UK insurance clients: define architectures, govern data/AI, run metadata discoveries, assess data assets, support engineering delivery, and drive change management and adoption across multidisciplinary teams.

Build and optimise scalable, serverless data pipelines and storage on GCP. Implement ETL, CI/CD and DataOps practices, support model productionisation with data scientists, document architectures, and guide migration toward event-driven managed cloud services.

Lead corporate actuarial activities including business planning, performance monitoring, and portfolio optimisation. Provide actuarial insight for pricing, reserving and strategy, develop tools and frameworks, collaborate with underwriting, risk and finance, ensure governance and compliance, and manage and develop a team.

Monitor and manage risk across systematic trading strategies, develop and maintain internal risk models and tooling, conduct risk research, collaborate with portfolio, trading and tech teams to resolve risk issues, and report risk data to stakeholders while enhancing the firms risk framework and culture.

The Rapid Application Developer will utilize rapid development techniques for projects, build trading frameworks, support applications, and manage data systems.

This role requires managing financing transactions, developing relationships with brokers, optimizing financing strategies, and conducting cost-benefit analysis on financing opportunities.

Design, build, test, and operate scalable identity and authorization services for a global fintech platform. Lead architecture and code reviews, participate across the SDLC, maintain CI/CD best practices, and collaborate with cross-functional teams to deliver secure IAM and FGAC solutions.

Lead design and delivery of production LLM-powered agent systems and firm-wide agent standards. Build reference agent apps, connect agents to internal data/APIs, establish security and governance for AI, adopt deployment and observability infrastructure, and partner with stakeholders to identify high-value use cases.

Lead technical direction across platform squads, ship and operate critical platform services, improve CI/CD and delivery workflows, drive reliability (SLOs, observability, runbooks), remediate production issues, mentor engineers, and participate in on-call and incident response to raise platform quality and developer experience.

The Human Data Operations Strategist manages data annotation projects, optimizes workflows, ensures high data quality, and collaborates with clients and teams for AI model development.

Design, build and deploy machine learning and AI solutions end-to-end: data exploration, feature engineering, model selection, evaluation, deployment, maintenance, and tooling to scale ML across products.

Build and lead the Data Labeling team, define annotation guidelines and QA frameworks, partner with researchers to create labeling workflows, prioritize projects, monitor metrics, improve tooling and automation, manage vendors, run complex AI evaluation projects (RLHF, safety, benchmarks), and communicate insights to leadership.

Lead technical development and production deployment of ML models for search, personalization, ranking, and recommendations. Build scalable, explainable ML solutions, own end-to-end impact, collaborate with backend and product teams, and iterate on experiments using cloud-native data at scale.

Lead technical ML efforts to detect and prevent financial crime by designing, developing and shipping production deep learning, graph and sequence models. Provide IC technical leadership, mentor peers, work with product, engineering and MLOps to iterate models on a cloud-native platform, and measure production impact while minimising false positives and operational costs.

Design and build a centralized observability platform for satellite and deep-space networks. Implement metrics, logging, and tracing (Prometheus, Loki, Tempo/OpenTelemetry), define SLOs/SLIs/error budgets, automate deployments with IaC and GitOps, integrate observability into Kubernetes and cloud environments, support engineers with instrumentation and tooling, lead monitoring/alerting/incident response, and participate in on-call rotations.