Senior Data Analyst

Job Information

Date Opened

12/05/2026Job Type

PermanentWork Experience

5\+ yearsIndustry

InsuranceCity

LondonProvince

City of LondonCountry

United KingdomPostal Code

N/A### Job Description

We are recruiting for a Senior Data Analyst on behalf of an award\-winning Lloyd's Syndicate.

The successful candidate must have experience working in a Lloyd's syndicate, managing agent, London Market broker or specialty (re)insurer.

You will help the team through its shift from platform delivery toward value\-added analytics and commercial insight. They will support the Data Analytics Manager by applying and role\-modelling technical standards, contributing to complex analysis, and introducing new techniques including the practical application of AI tools within the analytics workflow.

Key Responsibilities

• Acting as the senior analytics business partner to one or more underwriting classes, proactively identifying where analytics can improve pricing, portfolio steering, renewal decisions and exposure management.


• Translating open\-ended commercial questions into well\-scoped analyses and dashboard requirements, and collaborating with the wider business to identify opportunities for automation and operational efficiency gains.


• Identifying and applying practical AI tooling within the analytics workflow, including LLMs, agentic tools and code\-generation assistants, with a pragmatic view on where they add genuine value.


• Embedding the team's development lifecycle for BI and analytics assets, including robust source\-control practices for Power BI content (PBIP / TMDL format, Git\-backed repositories, feature branches, pull requests and meaningful commit history), and contributing to workspace governance across Dev / Test / Prod environments.


• Coaching analysts and BI developers on SQL, DAX, data modelling, visual design and engineering hygiene.


• Working closely with Data Engineering on changes to the semantic and curated layer and data marts.


• Delivering complex analytics workstreams end\-to\-end, and working within an Agile framework to break down requirements into epics and user stories, contribute to backlog prioritisation and provide realistic estimates.

Key Requirements *Essential*

• 5\+ years' experience in a data analytics or BI role, with at least 2 to 3 years in a Lloyd's syndicate, managing agent, London Market broker or specialty (re)insurer.


• Advanced SQL, including query optimisation and working with the Azure data stack (Data Factory, Synapse / Fabric, SQL\-based semantic layers).


• Advanced Power BI: data modelling (star schemas), advanced DAX, Power Query / M, performance tuning, RLS and deployment via pipelines.


• A strong understanding of Power BI engineering discipline: PBIP / TMDL source format, Git\-based version control, pull\-request review and structured release processes, with demonstrable experience in a team setting.


• Proven ability to carry out peer review and QA of analytics work, spotting model errors, DAX issues, performance problems and UX weaknesses.


• Excellent written and verbal communication skills, including presenting to underwriting and senior stakeholders, with a track record of turning ambiguous business problems into delivered analytical outcomes.

*Desirable*

• Python for data analysis and an appreciation of wider data science techniques, sufficient to collaborate credibly with Data Scientists and Actuarial colleagues.


• Hands\-on experience applying AI and LLM tooling to analytics work (such as Copilot for Power BI / Fabric, MCP\-style integrations or agentic assistants).


• Experience with Microsoft Fabric, dbt, Azure DevOps / GitHub Actions and data\-quality tooling.

This is an excellent opportunity to join a forward\-thinking analytics function within an established and respected Lloyd's Syndicate, at a genuine inflection point in how data drives underwriting decisions. If you have the technical depth and the commercial curiosity to thrive in this environment, we would be delighted to hear from you. *We do not retain any personal information without your permission. Please refer to our data protection policy on our official website for more information.*

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