Top Python Jobs in London

Develop algorithmic systems and software for BlackRock’s quantitative investment research teams. The role focuses on computer science, data management, mathematical modeling, computer simulations, distributed computing, GPU utilization, and machine learning. Responsibilities require delivering production-quality software using Python, Pandas, and Java or C/C++ while collaborating with computer scientists, data scientists, and quantitative investors.

Lead analytics for Wise’s Business Account Squad, partnering with Product, Engineering, and Design to shape roadmaps, define KPIs, measure product impact, and drive data-informed decisions. Own the analytics data strategy, roadmap, and tooling while leading, coaching, hiring, and capacity-planning for a team of 5+ analysts. Identify high-impact opportunities, evaluate initiatives, manage stakeholders, and improve decision-making speed across global business account products.

The Senior Data Platform Engineer will manage Databricks infrastructure, develop cloud systems, collaborate with teams, and enhance machine learning workflows.

Supports investment desk analytics, reporting, data quality, quantitative tools, and portfolio risk analysis. The role involves maintaining and enhancing investment models, automating data-heavy workflows, analyzing portfolio exposures, contributing to asset allocation research, documenting methodologies, and communicating insights to senior stakeholders. Candidates need strong quantitative skills, Python or MATLAB experience, advanced Excel capabilities, structured data handling, attention to detail, and an interest in financial markets. Investment analytics and multi-asset portfolio experience are preferred.

Support Delta One and equity finance trading by executing and hedging client trades, managing inventory, optimizing positions, and identifying market opportunities. Develop pricing, analytical, workflow, and automation tools using Python; perform daily controls including P&L estimates, inventory management, and corporate actions follow-up. Collaborate closely with sales, clients, and internal teams while building expertise in equity derivatives, financing markets, and hedging strategies.

Oversee global markets counterparty credit risk portfolios, including daily exposure administration, framework adherence, limit-breach escalation, risk-concentration monitoring, client data refreshes, management reporting, and restriction controls. The role partners with Sales and Trading, Credit Risk Management, Business Management, and senior stakeholders to strengthen governance and deliver timely risk-management outcomes.

As a Quantitative Researcher intern at Citadel, you'll develop models, implement trading strategies, and conduct statistical research in finance.

Leads full-stack software development across React or Angular frontends and Node.js/TypeScript backends while owning application lifecycle, risk, controls, resiliency, security, compliance, and operational governance. Designs, tests, deploys, and supports production systems; coordinates disaster recovery and technology refresh activities; mentors engineers; promotes AI-assisted development; and partners with risk, controls, and product stakeholders in an agile environment.

Own go-to-market strategy and field enablement for Cloudflare’s bot management and application security products. Build training, playbooks, battlecards, demos, proof-of-concept guides, competitive intelligence, certifications, and customer-facing materials. Lead customer conversations, develop subject-matter-expert programs, refine product narratives, and help sales teams communicate technical security concepts to practitioners and executives.

Build and ship end-to-end features for Akeneo Supplier Data Manager across data-processing pipelines, backend services, and TypeScript/React frontend systems. Help process large, messy supplier catalogues using deterministic workflows and LLM-based extraction and classification. Own features through production monitoring and support, participate in customer discovery, collaborate across the Product Cloud, and develop engineering skills through pairing, code review, and mentorship.

Design, build, and operate Akeneo’s Supplier Data Manager at enterprise scale. Develop reliable data-processing pipelines for messy supplier catalogues, including deterministic and LLM-powered extraction and classification. Create collaboration and governance workflows, ensure production observability and operational excellence, participate in customer discovery, and collaborate across teams. The role requires strong software engineering fundamentals, architectural thinking, debugging ability, end-to-end ownership, and clear communication.

Build and deploy production-grade, LLM-enabled applications for strategic customers. Own backend services, data orchestration, frontend integrations, APIs, vector databases, LLM pipelines, and reusable AI tooling. Work directly with customers in agile field deployments, integrate legacy systems, improve developer experience, and influence platform strategy. Deliver secure, scalable solutions while creating libraries, SDKs, prompts, scaffolds, and documentation that accelerate future enterprise AI implementations.

Analyze customer, product, and market data to identify sending-experience opportunities, size and prioritize product initiatives, define success metrics, evaluate experiments, and guide product decisions. The role partners closely with product managers, engineers, and analysts to shape new money-transfer products and improve existing experiences. Responsibilities also include communicating insights, validating data quality, and potentially improving instrumentation, transformations, and analytics pipelines.

Designs and presents hybrid and multi-cloud solutions for CSP and MSP partners. Leads technical sales activities, demonstrations, proofs of concept, and initial implementations while serving as a bridge between customers, partners, sales, product, and development teams. Advises on enterprise networking, cloud infrastructure, automation, security, observability, and AI-driven operations, communicates business value, troubleshoots complex architectures, and supports partner-led go-to-market initiatives.

Deliver customer enablement for hyperexponential’s Developer+ programme through workshops, code reviews, drop-in support, and technical guidance. Help customers move from hx-led development to independent delivery, covering architecture, coding practices, testing, deployment, and model lifecycles. Build repeatable delivery processes, convert insights into Academy content, use AI to scale support, and communicate recurring customer feedback to Product.

Analyzes and consolidates international co-brand credit card portfolio data across multiple markets. Develops Power BI and Excel dashboards, reporting tools, and analytical models; produces weekly and executive performance updates; monitors KPIs and identifies trends, risks, and opportunities. Partners with product managers, regional stakeholders, and external partners on performance reviews, campaign analysis, forecasting, and portfolio strategy. Improves reporting processes through automation, new datasets, and business intelligence solutions.

Designs and manages secure, automated CI/CD pipelines across AWS and GCP. Leads DevSecOps, GitOps, Infrastructure as Code, cloud security, container orchestration, monitoring, testing, and automation initiatives. The role develops scalable cloud-native architectures using Terraform, Ansible, Kubernetes, Docker, Helm, and related tools; troubleshoots infrastructure; ensures compliance and resilience; and collaborates with software, testing, security, and cloud engineering teams.

Lead pre-sales architecture for MongoDB Atlas and specialize in application search, including lexical and semantic search. Advise customers on scalable systems, conduct technical discovery, demos, proofs of value, presentations, sizing, and documentation, and support complex enterprise deal cycles. Enable other solution architects, mentor colleagues, relay customer feedback to Product Management, and influence Vector Search and AI/ML direction. The role is remote in Barcelona, Dublin, or London and requires approximately 25% travel.

Designs and scales highly available backend microservices, APIs, event-driven systems, and data pipelines supporting global travel and expense transactions. Leads technical architecture and cross-functional initiatives, improves performance and reliability, drives observability and production operations, and mentors engineers. The role also includes building micro front ends and collaborating with product, data, and platform teams on scalable travel platform solutions.

Lead product analytics for customer onboarding and account access. Derive insights from data, guide product decisions, partner with product managers, engineers, and designers, and identify opportunities to improve customer experience while preventing fraud. Build data pipelines, dashboards, and KPI reporting systems; communicate findings across teams; and explore AI-driven automation and machine learning techniques to improve analytics and generate insights.

Lead product analytics for Wise’s Send tribe, focusing on verification, transfer predictability, service quality, customer retention, and growth. Analyze customer problems, define KPIs, conduct A/B tests and causal analyses, track product impact, and guide prioritization with Product Managers and stakeholders. The role also supports scaling service operations, improving customer journeys, and identifying opportunities through SQL and Python analysis, with optional use of Airflow, dbt, Looker, and predictive modeling.

Lead data architecture and engineering for Wise’s marketing platform, building resilient high-volume streaming and batch pipelines with Python, dbt, Airflow, Kafka, Trino, and Iceberg. Develop unified customer data platform datasets, own MarTech integrations, establish data quality and reliability standards, scope ambiguous technical problems, and mentor software engineers. Partner closely with marketing, product, analytics, and engineering stakeholders to deliver scalable acquisition infrastructure.

Lead the architecture and production deployment of deep learning and machine learning systems for real-time financial crime detection. Design sequence-based, graph-based, and attention-based models; establish reusable experimentation-to-production pipelines; evaluate foundation models and embeddings; make architecture decisions under latency and throughput constraints; partner with data scientists on evaluation and measurement; and mentor engineers and data scientists.

Lead development and deployment of machine learning and Generative AI systems for AML operations. Responsibilities include building EDD LLMs, evaluation datasets and automated testing frameworks, prompt optimization, shadow testing, production monitoring, human-in-the-loop workflows, and financial crime prevention solutions. The role also provides technical leadership, mentorship, architectural guidance, and cross-functional collaboration.

Designs and develops secure, scalable agentic commerce solutions for payments. Responsibilities include building agent orchestration components and MCP servers, developing Python services, creating Databricks data pipelines, supporting MLOps workflows, evaluating agent behavior, implementing observability, and improving operational stability. The role requires cloud-native engineering, API and event-driven services, LLM application development, responsible AI practices, Kubernetes, and secure production software delivery.