Senior Data Scientist
- London, United Kingdom
Posted yesterday
About the role
Job Information
- Date Opened 26/08/2026
- Job Type Permanent
- Industry Insurance
- City London
- Province London
- Country United Kingdom
- Postal Code N/A
Job Description
We are recruiting for a Senior Data Scientist on behalf of a market leading Lloyd's Syndicate.
The successful candidate will strengthen the business's data science capability by delivering models and insights that improve underwriting profitability, automation and efficiency. It is a true end-to-end role, owning projects from problem framing through to deployment and ongoing model performance, with strong object-oriented programming, machine learning and statistical skills, and experience taking models into production, designing ML pipelines and working with MLOps, CI/CD and Azure.
Key Responsibilities
Delivery of data science products
- Leading data science projects end-to-end, from problem framing through development, deployment and ongoing monitoring in production.
- Working alongside the actuarial team and coordinating with the Data Science and Data Analytics Manager to support the business with proactive analytics and insights.
- Using generative AI to enrich insight and unlock new opportunities, deployed and maintained through the same MLOps patterns applied to traditional models.
Engineering and MLOps standards
- Designing, building and maintaining machine learning pipelines in a cloud environment, applying sound software engineering practice.
- Owning deployed models in life, monitoring performance and drift, and ensuring models are documented and explainable to a standard appropriate for a regulated environment.
Stakeholder engagement and requirements
- Working with technical and non-technical stakeholders to identify, document, analyse and prioritise requirements for data science products.
- Producing clear deliverables and communicating findings and their limitations to audiences without a technical background.
Team and capability building
- Coaching and upskilling data scientists and data analysts through code review, pairing and mentoring, and contributing to the data science backlog and roadmap.
Key Requirements
Essential
- Strong Python, written to production standard, with object-oriented design and software engineering fundamentals: version control, code review, automated testing, dependency and environment management.
- Machine learning across the standard toolkit (scikit learn, pandas, NumPy, statsmodels or equivalents), with sound judgement about model selection, validation and the limits of what the data supports.
- MLOps and CI/CD in practice, covering pipeline orchestration, model versioning, automated deployment, monitoring and retraining.
- Cloud based machine learning delivery, ideally on Azure (Azure ML, Azure DevOps), with equivalent AWS or GCP experience considered.
- SQL and relational data modelling, with the ability to work efficiently against large datasets.
- Statistical foundations sufficient to design sound experiments, quantify uncertainty and challenge conclusions that the data does not support.
Desirable
- Insurance experience (specifically in the Lloyd's market), pricing or underwriting in a regulated environment.
- Practical experience deploying generative AI or LLM based solutions.
Altogether, this role suits a hands-on data scientist who can own the full lifecycle from problem framing to production and translate that work into commercial value alongside underwriters and actuaries.
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