Insurance Data Analyst

Role Summary

Insurance Data Analysts transform raw insurance data into insights that support underwriting, pricing, claims, and risk decisions. They work with large datasets, build dashboards, and perform exploratory analysis to uncover trends in loss experience, customer behavior, and portfolio performance.

Core Responsibilities

• Clean, structure, and validate underwriting, claims, and exposure data.
• Build dashboards and reports for underwriting, claims, and actuarial teams.
• Perform exploratory data analysis to identify trends and anomalies.
• Support predictive modeling efforts with data preparation and feature engineering.
• Collaborate with IT and business teams to improve data quality and governance.

Key Skills & Competencies

• SQL, Python, or R
• Data visualization (Power BI, Tableau, Qlik)
• Understanding of insurance data structures (policy, premium, loss, exposure)
• Statistical literacy and problem-solving

Common Backgrounds

• Data Science, Statistics, Mathematics, Actuarial Science, or MIS
• Experience with insurance datasets is a major advantage

Relevant Designations

• AIDA (Associate in Insurance Data Analytics)
• AINS (for insurance fundamentals)
• CPCU (for broader insurance context)
• Data science certificates (non-designation)