Data Analyst (P&C insurance)

Qualifications & Requirements

Experience

• 2-5 years of experience as a Data Analyst, Business Analyst, Systems Analyst, or similar analytical role.
• Experience within the Property & Casualty (P&C) insurance industry strongly preferred.
• Experience supporting underwriting systems, insurance operations, or data/reporting environments.

Technical Skills

• Strong SQL skills with the ability to extract, manipulate, and analyze large datasets.
• Experience with Power BI or similar business intelligence and visualization tools.
• Advanced Microsoft Excel skills, including XLOOKUP, VLOOKUP, pivot tables, complex formulas, and data analysis techniques.
• Experience performing data validation, reconciliation, testing, and root cause analysis.
• Familiarity with Agile methodologies and tools such as Jira, Azure DevOps, and Confluence.
• Understanding of system integrations, APIs, and data transformation processes is preferred.
• Exposure to underwriting platforms such as Guidewire, Duck Creek, or Majesco is a plus.
• Interest in and understanding of emerging AI and analytics capabilities is beneficial.

Insurance & Business Knowledge

• Strong understanding of Property & Casualty insurance operations.
• Knowledge of underwriting lifecycles, policy administration processes, rules engines, and policy lifecycle management.
• Understanding of how data flows across insurance systems and business processes.

Soft Skills

• Strong analytical and problem-solving abilities.
• Excellent written, verbal, and presentation skills.
• Ability to manage multiple priorities in a fast-paced environment.
• Strong stakeholder management and relationship-building skills.
• Detail-oriented with a commitment to data accuracy and quality.
• Process improvement mindset with a proactive approach to identifying and solving issues.
• Ability to work effectively with both technical and non-technical teams.

Success Measures

In this role, success will be measured by:

• Improved data quality and reporting accuracy.
• Timely identification and resolution of data and system issues.
• Effective support of underwriting and business operations.
• Delivery of actionable insights that drive business decisions.
• Strong stakeholder satisfaction and cross-functional collaboration.
• Continuous improvement of data processes, controls, and reporting capabilities.