Data Analyst (Tech Insurance Operations)
At a glance
Mid-level Data Analysis & BI role at Acrisure. London · full-time · no salary stated · we estimate £41,362–£63,750.
Acrisure has not published a salary for this role. The figure below is our estimate, not theirs.
dataroles summary, based on the employer's posting.
What you'll do
- Query claims data from systems, TPA feeds, bordereaux and warehouses, checking quality and building regular extracts
- Turn claims data into trend, severity and exception analysis that supports reserving, operations and underwriting decisions
- Create recurring claims dashboards, KPI packs and reports for executives, boards, capacity partners and actuarial teams
- Support reserve reviews, loss development and large-loss monitoring, then feed claims insights into underwriting choices
- Translate claims needs into data rules and test cases, and help test systems, scoring tools and reporting workflows
What you bring
- At least three years in data analytics within financial services or insurance
- Strong SQL skills, advanced Excel ability and experience reconciling data
- You can work through incomplete or inconsistent sources and explain complex findings clearly for business decisions
Who this fits
This hands-on role suits a mid-career analyst who wants to work across claims operations, reserving and underwriting. You’ll report to the Head of Claims and collaborate with TPA contacts plus underwriting, operations and technology teams. Azure Databricks experience is preferred, not required.
From the employer
Data Analyst (Tech Insurance Operations)
Role Overview
We are seeking a highly analytical and technically capable Data Analyst to support the development of a data-driven claims function. This role will report directly to the Head of Claims and will work closely with TPAs, and Vave’s Underwriting, Operations, and Technology teams.
The Data Analyst will be responsible for extracting, analysing, reconciling, and interpreting claims data to support operational oversight, reserving discipline, TPA performance, underwriting feedback, and portfolio profitability. The ideal candidate will have strong experience with SQL, Excel, data validation, reporting and claims analysis
This is a hands-on role for someone who can transform data into insight, and help the business make better claims, underwriting, and financial decisions.
Key responsibilities
Data Analysis
- Analyse claims data from internal systems, TPAs data feeds, bordereaux reports, and data warehouses.
- Use SQL to query claims databases, validate data quality, build recurring extracts, and support ad hoc analysis.
- Work within an Azure Databricks environment, utilising SQL, and Python skills to automate claims analysis and oversight reporting.
- Operational reporting, severity analysis, reserving reviews, claims feedback for underwriting.
- Identify and investigate data quality concerns.
- Translate claims data into clear insights, trends, exceptions, and recommended actions.
Claims MI, Reporting & Dashboards
- Shape recurring claims management information, dashboards, KPI packs, and executive reporting.
- Track and report on key claim metrics.
- Support the creation of board, capacity partner, underwriting, and actuarial reporting packs.
Actuarial & Underwriting Support
- Support reserve reviews, loss development analysis, large loss monitoring, data reconciliations, and claims trend analysis.
- Partner with Underwriting to provide claim insights that inform risk selection, pricing, appetite, policy wording, exclusions, endorsement, and portfolio strategy.
- Support development of claims feedback loops that connect loss experience back to underwriting action.
Rules Engine, Scoring & Claims Intelligence
- Support the build-out of claims rules, escalation triggers, severity scoring models and exception reporting.
- Participate in UAT for claims systems, rules engines, dashboards, portals, data feeds, and workflow tools.
- Translate business requirements from Claims into technical data logic, SQL predicates, reporting rules, and test cases.
Required experience
- 3+ years of experience in data analytics within the financial/insurance sector
- Ability to work with incomplete, inconsistent, or complex data sources.
- Strong SQL querying and data manipulation skills.
- Advanced Excel and data reconciliation skills.
- Preferred knowledge of any of the following: laims analytics, insurance data analysis, claims operations, actuarial support, underwriting analytics, TPA oversight, or related insurance analytics roles.
- Experience working within Azure Databricks (preferred), using notebooks to analyse and transform data, and leveraging Azure data services such as Azure SQL, Data Lake Storage, and cloud-based data platforms.
- Experience extracting and analysing data from systems or reporting platforms, including Lloyd’s/delegated authority bordereaux.
- Demonstrated ability to analyse complex datasets and present findings in a clear, concise, business-relevant manner.
Preferred experience
- Prior experience with a TPA, MGA, MGU, insurance carrier, or reinsurer within a delegated authority business.
- Experience working with Actuarial and Underwriting teams.
- Familiarity with claims bordereaux, delegated authority reporting, capacity partner reporting, or reinsurance reporting.
- Experience with Databricks, Synapse, or similar analytics tools.
- Understanding of claims leakage, severity management, reserve adequacy, litigation trends, fraud indicators, subrogation, and vendor performance.
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