Lead Data Analyst (Hybrid)

The Lead Data Analyst serves as a key analytical voice within Claims, transforming data into actionable insights that drive operational and strategic decisions. This role goes beyond reporting what happened. It focuses on diagnosing why metrics moved and recommending what to do about it. You'll lead high-impact analyses on claims volume, severity, cycle times, and KPIs while partnering with Claims leadership and cross-functional teams including Loss Reserving, Product Management, and Pricing. The ideal candidate combines deep Auto claims domain expertise with intellectual curiosity, strong storytelling skills, and a willingness to leverage modern tool, including frontier AI models, to deliver faster, sharper insights.

In this hybrid role, you will be expected to work a minimum of 10 days per month from one of the following office locations: Madison, WI 53783

Internal candidates are encouraged to apply and should review the internal mobility guidelines in the hybrid policy reference guide for more information

• Lead variance and root-cause analyses to explain changes in claims performance metrics (volume, severity, cycle times, KPIs), moving the team from descriptive to diagnostic and prescriptive analytics
  
• 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
  

• Domain expertise: Strong background in Property & Casualty insurance claims, with Auto claims experience required; understands how the business operates and generates value
  
• Analytical thinking: Proven ability to move beyond surface-level reporting to uncover root causes and recommend solutions
  
• Technical proficiency: 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).
  
• Emerging tech fluency: Exposure to Python, BigQueryML, or similar tools a plus; genuine interest in expanding technical toolkit
  
• Communication & storytelling: Ability to distill complex analysis into clear, persuasive narratives for both technical and non-technical audiences
  
• Collaboration: Experience working cross-functionally; able to "speak the language" with Data Engineering and technical teams without needing to own ETL work directly
  
• Curiosity & growth mindset: Self-directed learner who stays current with industry trends, new tools, and modern analytical approaches including AI/ML applications
  

• Up to 10%.
  

• Work that primarily involves sitting/standing.
  

• Offer to selected candidate will be made contingent on the results of applicable background checks
  
• Offer to selected candidate is contingent on signing a non-disclosure agreement for proprietary information, trade secrets, and inventions
  
• Sponsorship will not be considered for this position unless specified in the posting