Lead variance and root-cause analyses to explain changes in claims performance metrics (volume, severity, cycle times, KPIs)
Build and maintain models that quantify business impact of operational initiatives, vendor performance, and process changes
Develop forecasts to support planning and resource allocation decisions
Partner with Claims leadership as a trusted analytical advisor; translate complex findings into clear, compelling narratives that drive action
Support internal business partners (Loss Reserving, Product Management, Pricing) with claims data expertise and ad-hoc analysis
Collaborate with Data Engineering teams to ensure data quality, pipeline integrity, and alignment between business needs and technical solutions
Mentor fellow analysts and contribute to a culture of curiosity, continuous learning, and knowledge sharing
Proactively explore emerging tools and techniques, including AI-assisted workflows, to improve team efficiency and analytical depth
Follow and curate industry data to understand internal performance relative to industry benchmarks or trends

Strong background in Property & Casualty insurance claims, with Auto claims experience required
Proven ability to move beyond surface-level reporting to uncover root causes and recommend solutions
Advanced SQL skills (BigQuery preferred)
Experience with BI/visualization tools (Looker, Tableau)
Comfort with Google Sheets/Excel for modeling and analysis, and exploratory data analysis (EDA)
Exposure to Python, BigQueryML, or similar tools a plus
Ability to distill complex analysis into clear, persuasive narratives for both technical and non-technical audiences
Experience working cross-functionally; able to 'speak the language' with Data Engineering and technical teams without needing to own ETL work directly
Self-directed learner who stays current with industry trends, new tools, and modern analytical approaches including AI/ML applications

Lead Data Analyst – Hybrid

Key skills