Top Python Jobs in London

The Senior Data Scientist will collaborate with product teams, develop metrics, design data pipelines, and influence product strategy through data analysis at Intercom.

As a Senior Data Scientist at Intercom, you'll analyze data to drive decisions, support product teams, build data pipelines, and influence product strategy using AI tools.

The FRG Associate conducts bottom-up fundamental research, collaborates with investment professionals, and generates insightful analysis to support investment decisions.

Develop and maintain features for a notification platform, upgrade applications, enhance monitoring, and support migration for a public sector client.

The Software Engineer III (Backend) develops complex software solutions, leads projects, collaborates with teams and creates technical documentation while adhering to best practices.

The Data Centre Engineer will manage data centre operations including design, installation, and maintenance of equipment while ensuring data safety and accessibility.

The role involves developing and supporting applications for commodities trading, enhancing integrations, maintaining data pipelines, and collaborating with various teams for effective solution delivery.

The Software Engineer will build customer-facing products for healthcare, focusing on full-stack feature development and user experience, while engaging with customers and iterating on the product based on feedback.

Lead fraud monitoring and detection efforts, develop prevention strategies, analyze data to identify loss drivers, and mentor junior team members.

Build and own backend platform systems around AI models: design APIs, data models and schemas, implement integrations and data pipelines, create internal libraries/tooling, and drive features end-to-end from design to production while collaborating with engineers and AI specialists.

Build and own full-stack platform systems around AI models: design APIs, database schemas, frontend components, shared libraries, connectors, and data pipelines. Collaborate with design and AI teams, drive features end-to-end from design to production, and shape technical direction and engineering practices.

Implement and manage photorealistic lighting, shading, and scene assembly for high-end VFX shots. Integrate assets from multiple departments, optimize shading and render setups, collaborate with CG Supervisors and Compositors, reproduce real-world lighting, render required passes, and meet production schedules while troubleshooting pipeline and asset issues.

Lead the development of strategic quantitative initiatives to enhance trading efficiency, models, and data infrastructure across equity derivatives markets.

Build and maintain scalable, secure data pipelines, warehouses, and streaming systems. Collaborate with engineering, data science, analytics, and product teams to translate requirements, optimise architectures, and deliver the data platform. Mentor peers, promote best practices (CI/CD, testing, observability, IaC), and contribute to the data engineering roadmap.

Handle complex, custom client requests by building end-to-end reports, performing quantitative analysis and data mining using SQL/pySpark and Python, developing research tools on Similarweb raw data, and partnering with Engineering and Advisory teams to scale solutions and deliver strategic data products.

Lead canonical data modelling and governance for buy-side data domains, translating logical models into Snowflake-ready schemas, DDL, API contracts and data quality rules. Work with investment, operations and ESG teams to define lineage, golden sources, industry-standard mappings (ISO20022, SWIFT, FINOS CDM), and embed governance while mentoring engineers to ensure implementation fidelity.

As a Data Scientist, you will create and enhance detection models for secure Generative AI adoption, collaborate with teams on data curation, and drive continuous model improvement based on customer feedback.

Lead Creature TD provides creative and technical guidance for creature asset setup and shot work, leads and mentors the creature team, implements rigs and character simulations (cloth, hair, flesh), collaborates across departments, troubleshoots technical/aesthetic issues, assists production staffing and scheduling, and maintains asset and shot quality.

Lead cross-functional engineering teams to design, deliver, and evolve cloud-native, event-driven insurance applications. Own architecture, roadmap, and delivery for policy, claims, underwriting, and compliance systems while ensuring regulatory adherence, vendor management, Agile/DevSecOps practices, and engineering KPIs.

Build and maintain scalable Python backend microservices: productionize data science prototypes, fix production issues, improve monitoring, and ensure tested, well-documented code following engineering best practices.

As a Senior Data Engineer, you will design data pipelines, collaborate with teams, build demos, and improve data processes within a cloud-native environment.

Build and automate end-to-end GTM systems across marketing, CRM, sales engagement, and analytics. Design scalable workflows, integrations, and automations, embed AI for lead scoring and prioritisation, improve data quality and reporting, and enable Sales, Partnerships, and Customer teams via training and tooling. Partner with Engineering and Commercial teams to deliver and optimise revenue-driving systems.

Support pricing, valuation and xVA analysis for interest rate and structured derivatives. Build analytics, models and tools, analyse transaction economics and valuation drivers, manage trade lifecycle events, and collaborate with Quants, Risk and Finance to improve pricing, controls and automation.

Provide first-line technical support for Forter customers: manage and resolve inbound tickets to SLAs, troubleshoot platform issues, collaborate with engineering and product teams to identify bugs and implement solutions, train clients, standardize documentation, document resolutions, set follow-ups, and participate in on-call rotations.

Maintain and scale data and ML infrastructure, build CI/CD pipelines, implement observability, ensure high availability and disaster recovery, manage access and secrets, troubleshoot incidents, and provide 24/7 coverage across time zones.