Claims Analytics Lead

markelcorp; Greater London; On-site; GBP 90,000 - 135,000; Full time

Job summary

Markel International is building a dedicated claims analytics capability within the International Portfolio Analytics team, working with International Claims to improve claims decisions, operational performance and underwriting insight. This hands-on role combines technical delivery with commercial and stakeholder skills.

You will shape the analytics roadmap, run analyses, build and test models, and translate results into practical tools used by claims teams.

Qualifications

• Strong experience in claims analytics within general insurance.
• Hands-on experience with Python, R and SQL.
• Ability to work with unstructured data from notes and reports.
• Proven track record embedding analytics into day-to-day decision making.
• Experience applying analytics to forecasting, triage, severity or recoveries.

Responsibilities

• Own and develop the Claims Analytics roadmap with International Claims.
• Lead analytics work from data assessment to model building and testing.
• Strengthen data foundations by integrating claims, policy, exposure and financial data.
• Turn analytical work into practical tools and recommendations used by claims teams.
• Communicate findings and priorities clearly to senior leaders.

Skills

Claims analytics

Python

R

SQL

Data science

Tools

Python

R

SQL

Job description

This is an opportunity to build out a dedicated claims analytics capability for Markel International. This is a new function sitting within the International Portfolio Analytics team and working directly with International Claims. You will use claims data and analytical modelling to improve claims decisions, operational performance and underwriting insight.

This is a hands-on role combining technical delivery with strong commercial and stakeholder skills. You will shape the Claims Analytics roadmap with senior claims colleagues, carry out analysis, build and test models, and turn the results into practical tools and recommendations. You will have the scope to take work from an initial business question through to a solution that is used by claims teams, drawing on support from colleagues across Data Platforming and BI, Portfolio Management and the AI Centre of Enablement where specialist input is needed.

You will work across the International business and build a strong understanding of its products, markets, claims practices and operating models. Your initial focus will combine establishing reliable claims data and analytical foundations with delivering practical use cases in areas such as forecasting, resource planning, lifecycle analysis, triage, recoveries and claims performance. Working alongside the existing Claims MI team, you will focus on deeper analysis, modelling and decision support.

We're all about people | We win together | We strive for better | We enjoy the everyday | We think further

Who we are:

Business Unit overview:

The International Portfolio Analytics (IPA) team is a dynamic, multi-functional group that operates with creativity, autonomy, and empowerment. Embedded within the underwriting business and represented in senior leadership forums, the team supports all five divisions withing Markel International - London Market, Asia Pacific, UK, Canada and Europe. The team has four core pillars:

• Portfolio Management
• Pricing Transformation
• AI Centre of Enablement
• Catastrophe & Exposure Management

Part of Markel Group (NYSE - MKL) a Fortune 500 company with over 60 offices in 20+ countries, is a holding company for insurance, reinsurance, specialist advisory, and investment operations around the world.

What you'll be doing:

• Own and develop the Claims Analytics roadmap, using your judgement to agree priorities with International Claims and focus effort on practical use cases with clear business value.
• Act as the lead analytics partner to International Claims, building trusted relationships with its leadership, Operations, MI and local teams.
• Lead the analytical work on priority use cases, from initial investigation and data assessment through to building, testing and improving statistical and machine learning models.
• Strengthen the claims data and analytical foundations by bringing together claims, policy, exposure, finance and other relevant data, and by drawing structured information from claim notes, adjuster reports and correspondence, to provide a clear and consistent view of claims performance.
• Develop analysis and models across the claim's lifecycle, including forecasting, resource planning, claim progression, triage, severity, recoveries and operational performance.
• Ensure that insight into claims performance, loss drivers and causes of loss advises claims, underwriting, portfolio management, actuarial and reserving decisions.
• Turn analytical work into practical tools, insight and recommendations that claims teams use, working with Claims MI and wider Data teams, Technology and the AI Centre of Enablement to place analytics into regular business processes.
• Set clear measures of success, maintain suitable data and model controls, and communicate progress, findings and priorities clearly to claims professionals and senior leaders.

Key Skills:

• Strong experience in claims analytics, insurance analytics, data science or a related analytical role within general insurance. This may have been gained in personal lines, commercial insurance, specialty insurance or the London Market.
• Hands-on experience of analysing data and developing statistical or machine learning models in a commercial setting, supported by strong practical skills in Python or R, together with SQL. Experience drawing conclusions from large and small datasets
• Comfort working with unstructured claims data such as handler notes, loss adjuster reports and correspondence, and an awareness of how text analytics and large language models can turn it into usable data. Specialist NLP expertise is not required
• A track record of embedding analytics into day-to-day decision making, with examples of models, tools or insight that operational teams adopted and kept using, and an understanding of why analytical work sometimes fails to land
• Experience of applying analytics to claims or related insurance problems, such as forecasting, triage, severity, fraud, recoveries, claim duration, resource planning or operational performance.
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