Top Python Jobs in London

The Data Scientist designs and deploys data models and automation solutions, collaborating with teams to meet business needs through data-driven insights.

The Technical Lead Manager will manage a team of developers, oversee project management, develop features, ensure code quality, and maintain documentation.

The role involves building and implementing machine learning models, collaborating with cross-functional teams to solve complex problems in data science.

The Treasury Associate will manage treasury operations, oversee cash forecasting, sign off on capital calls and distributions, and execute FX trades. They will coordinate compliance, manage stakeholder relationships, and contribute to operational improvements and system upgrades.

Lead high-impact AI solutions, overseeing architecture and deployment. Partner with stakeholders, coach engineers, and drive project success from inception to launch.

Lead technical pre-sales for Algolia by partnering with Sales to demo the product, run POCs, build prototypes/integrations using Algolia APIs, qualify customer goals, respond to RFPs, and transition accounts to post-sales. Advocate customer needs to Product and Engineering, produce technical content, and enable internal teams while supporting customer adoption and success.

Design and enhance tools for developer productivity and infrastructure; improve CI/CD pipelines, optimize performance, and mentor team members.

Apply causal inference methods to measure incremental Customer Lifetime Value, design and analyze experiments and observational studies, quantify drivers of player value from large-scale data, and translate causal insights into actionable recommendations for stakeholders.

Develop and deliver machine learning models (churn, propensity, CLV, recommendations) using large-scale behavioral and transactional data. Translate business problems into modelling solutions, collaborate with engineering, product, and commercial teams, communicate insights to stakeholders, and explore advanced methods (deep learning, sequence models) to drive player engagement and value.

Lead a team of data analysts as the maritime SME for vessel and company datasets: ensure data accuracy, design and maintain ETL and ingestion pipelines, implement automation and validation using SQL and Python, integrate new data sources, create dashboards, manage KPIs/OKRs, and collaborate with Product, Engineering, Data, and Commercial teams to deliver high-quality maritime intelligence.

Provide cloud and AI technical consulting, design solutions and migrations on Tencent Cloud, support pre-sales and cross-functional project coordination, enable partners via training, and document industry-specific use cases.

Support B2B bid pricing and commercial finance activities: build and maintain financial models, review and sense-check assumptions, support governance, maintain pricing intelligence, perform post-bid analysis, and collaborate with cross-functional teams to ensure commercially robust proposals.

Own the end-to-end technical relationship for a single global financial-services account: drive discovery, design PoCs, architect Snowflake-based data and AI solutions, lead technical evaluations, mentor junior SEs, and coordinate across Product, Services, Support, and Engineering to accelerate adoption and expansion.

Act as the internal authority on election integrity, violent extremism, and fraud: design and run review workflows, lead evaluations and escalations, collaborate with Safety, Alignment, Policy, Legal and Engineering to validate models, build detection and enforcement systems, manage review operations and partners, and represent the lab externally on reporting and information sharing.

As a Senior Data Engineer, you will enhance data governance, improve data quality, and ensure compliance. You'll lead implementations, develop observability systems, and mentor teams to strengthen data reliability across the organization.

Lead technical implementation and production of QS rankings: develop and test statistical methodology, manage data pipelines (dbt/Snowflake/AWS), ensure data quality, mentor analysts, produce stakeholder-facing documentation and presentations, represent QS externally, and build reusable analytical tooling and scenario analyses.

Lead technical development and production deployment of advanced ML solutions (including LLMs, RAG, graph and sequence models) to improve customer operations. Provide hands-on engineering, mentor ML engineers, collaborate with product and backend teams, and drive MLOps and lifecycle strategy to route, disambiguate and resolve customer queries at scale.

Lead and deliver technically complex backend and full-stack projects, simplify architecture, mentor engineers, use AI-assisted tooling, and partner with product and design to build reliable, high-impact solutions.

Lead delivery of advanced AI solutions, provide technical and architectural leadership, drive adoption of cloud-native AI engineering, and manage, coach, and develop a multidisciplinary data science team while ensuring responsible AI practices and strong stakeholder engagement.

Monitor, triage and respond to cyber security incidents using SIEM tools; develop run books, detection use cases and dashboards; research threat intelligence; remediate events and improve GSOC defensive capabilities operating on a follow-the-sun shift rotation.

Lead and grow a data science team to design, develop, evaluate, and deploy production-grade AI/ML solutions (LLMs, Generative AI, RAG, transformers). Own technical vision, MLOps/LLMOps, model governance, and cross-functional execution with Product and Engineering to deliver scalable business impact in financial markets.

Work within multidisciplinary teams to design and run genomic and multi-omics analyses (WGS, GWAS, rare variant testing, fine-mapping, MR). Prepare, QC and harmonise datasets, build and refine pipelines and containers (Nextflow, cloud), benchmark methods, and produce reports and publications. Act as a domain expert supporting internal and external stakeholders on study design, analysis and interpretation in human disease genetics.

Develop, deploy, and maintain machine learning and statistical solutions to optimize the Cint Exchange. Analyze large datasets, model marketplace dynamics (price elasticity, supply/demand), design experiments (A/B tests), and produce clear visualizations and recommendations for cross-functional teams to inform product, pricing, and strategy.

Design, build, and maintain end-to-end ETL pipelines and a shared ETL framework. Write tested mapping and validation code, perform code reviews, mentor junior engineers, and collaborate with product, QA, and client teams to deliver accurate, production-ready data integrations to regulatory standards.

Lead development and adoption of agentic SEO/GEO delivery: build hands-on AI/agentic tooling, set technical standards for enterprise search, drive client adoption, design measurement and testing frameworks, and ensure automated outputs meet quality and commercial objectives.