Top Python Jobs in London

Turn research prototypes into scalable, fault-tolerant ML and physics infrastructure for drug discovery. Improve GPU utilization, distributed execution, reproducibility, orchestration, monitoring, and packaging so scientists can run reliable, multi-cluster workflows and agent-usable pipelines.

Design, implement, and deploy stateful agentic LLM orchestration and RAG systems integrated with internal APIs, databases, and third-party tools. Collaborate in Agile teams to deliver reliable AI-automation solutions, contribute to code review and QA, improve system reliability, and communicate technical trade-offs with stakeholders.

Lead Internal Auditdigital transformation and the Data Analytics Centre of Excellence. Drive Celonis adoption for continuous monitoring, use SQL/Python/Alteryx/Power BI for analytics, partner with IT to improve data governance, and advise senior leaders while building a high-performing audit analytics team.

Lead R&D to design and deploy generative models for graphics and video processing. Research and prototype novel methods, build data generation pipelines, collaborate on publications and patents, and support cross-team integration for game rendering and streaming applications.

Build reusable geospatial models, data pipelines and interactive tools across SYSTEMIQ platforms. Apply GIS analytics, geospatial Python libraries and AI-assisted methods to support project delivery, scale internal tooling, and incorporate new techniques into live sustainability projects.

Senior engineer responsible for evolving SolstiCE index calculation platform: define architecture, design and implement features, integrate upstream/downstream systems, ensure robustness, manage production incidents, liaise with trading and administration stakeholders, and coach junior engineers.

Develop and maintain credit models and underwriting strategies for unsecured lending, monitor portfolio performance, build dashboards and data tables, translate data insights to inform product and pricing decisions, and collaborate cross-functionally to support product rollouts and regulatory-compliant lending.

Lead product strategy and scoping for an M&A platform: map end-to-end M&A journeys, define detailed product and workflow specs, design and run experiments and lightweight prototypes, combine quantitative and qualitative analysis to reduce friction and drive growth, and work with the Product Builder, Deal Team and leadership to prioritise and launch product features.

Lead collation, analysis and submission of defined-benefit reinsurance data and reporting, manage treaty administration, drive data quality and process improvements, support pricing and finance teams, deliver regular reporting, provide training, and assist audits and contract requirements.

Productionize and support analytics and AI solutions by building reliable Python-based data workflows, deploying containerized/cloud services, modernizing legacy analytics, and collaborating with data science, engineering, and business teams. Provide EMEA support, create documentation and runbooks, and maintain Power BI dashboards and recurring analytical workflows.

Analyze and optimize operational workflows, implement data-driven improvements, monitor KPIs, own end-to-end processes, solve complex problems, and coordinate with Engineering, Compliance, Customer Success, and Product to deliver business value.

Design, build, and maintain large-scale data pipelines and distributed systems to ingest, process, and serve petabytes of vehicle data. Collaborate with ML and CV teams, mentor junior engineers, define long-term product strategy, and ensure robust, testable infrastructure using cloud and orchestration tools.

Design, implement and support DevOps practices to improve delivery, automation, monitoring and software quality. Build and maintain CI/CD pipelines, IaC (Terraform), Kubernetes/Helm deployments, and integrations across databases and services while collaborating with stakeholders, QA, IT Ops and InfoSec.

Implement and support DevOps improvements to increase delivery speed and software quality. Build and maintain CI/CD pipelines, IaC with Terraform, container orchestration with Kubernetes and Helm, AWS infrastructure, database schema changes, monitoring, and automation in Python. Collaborate with development, QA, IT operations, infosec and stakeholders to translate business needs into technical solutions and best practices.

Lead Operations analytics partnering with senior operations leaders to own MI, KPIs, forecasting and workflow optimisation. Hands-on role delivering SQL/Python analyses, measuring automation/AI impact, guiding resourcing decisions and translating results into action.

Design, build, and productionize end-to-end ML and LLM-powered recommendation features: architect data pipelines for massive datasets, train and serve models, integrate real-time stores and APIs, set up monitoring and A/B testing, debug distributed systems, and collaborate with Product, Design, and Engineering to deliver scalable personalization.

Own and build the integrated demand-forecasting models (D0–D30) that drive sorting, routing and network planning. Lead the hardest forecasting problems: long-horizon model generation, inbound international volume, parcel size/weight prediction. Define methodology, validation standards, model interfaces, and production quality while collaborating with ML engineers, analysts and operations to measure model impact on cost per parcel.

Lead hands-on delivery of data engineering engagements, build and mentor teams, set technical standards (testing, CI/CD, observability, governance), shape client proposals, represent YLD externally, and grow the data practice while stepping in on complex client work.

Design and build models, strategies, and systems to price and trade financial instruments. Work with researchers, engineers, and traders on dataset generation, time-series analysis, feature engineering, model building, hyperparameter tuning, and distributed/deep-learning training at large scale.

Work with full-time researchers to identify market signals, analyze large datasets, design experiments, generate datasets, perform time-series analysis, engineer features, build and test models, and help create and productionize trading strategies. Participate in classes, seminars, and collaborative learning activities.

Intern will be paired with full-time engineers to build production-quality software, learn OCaml (and sometimes Python), and work on diverse projects from trading systems to language design under close mentorship.

Work alongside full-time ML researchers on end-to-end projects using large market datasets and massive compute. Tasks include model design, implementation in Python and ML frameworks, hyperparameter tuning, debugging training issues, and analyzing model predictions for systematic trading challenges in nonstationary multi-agent environments.

Lead the crowd team to deliver high-quality VFX crowd work, develop shot templates and tools, maintain motion libraries, manage agent setups, mentor artists in Houdini, troubleshoot pipeline issues, and collaborate with R&D, Pipeline and Production to meet show goals.

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.