What You'll Do
• Build and maintain high-quality, scalable data models and semantic layers for analytics use cases.
• Deliver end-to-end insight work: problem framing, analysis, visualization, and communication.
• Partner with Product, Clinical Analytics, Medical Economics, Finance, and Operations on key priorities.
• Apply and champion AI-enabled workflows (for example, AI-assisted analysis and documentation) to
improve team productivity, insight velocity, and adoption of trusted analytics practices.
• Design intuitive dashboards and self-serve reporting experiences for business and clinical
stakeholders.
• Improve data quality, documentation, and analytics standards across core reporting assets.
• Use hypothesis-driven analysis to identify opportunities to improve patient outcomes and reduce
avoidable cost.
• Contribute to team best practices and support peers through collaboration and knowledge sharing.
Qualifications
• 5+ years of experience in analytics engineering, BI, or data-focused analytics roles.
• Strong SQL proficiency; experience with cloud data warehouses (Snowflake preferred).
• Experience with data modeling and transformation frameworks (dbt preferred).
• Experience building dashboards in Sigma, Tableau, Power BI, or similar tools.
• Strong analytical and problem-solving skills with attention to data quality and business context.
• Ability to translate ambiguous business questions into clear analytical plans.
• Strong written and verbal communication skills for technical and non-technical audiences.
• Bachelor's degree or equivalent practical experience.
Preferred Experience
• Healthcare analytics experience, especially in risk adjustment, clinical quality, utilization,
attribution, or medical economics.
• Familiarity with healthcare data structures and longitudinal/member-level analysis.
• Good to have: Python (or similar language) for automation or advanced analytics.
• Comfort operating in a fast-paced, evolving environment with a high degree of ownership.
What Success Looks Like
• Stakeholders trust and actively use your insights to make better decisions.
• Analytics outputs are timely, accurate, and linked to measurable outcomes.
• Data assets are documented, reusable, and easier for teams to build upon.
• Cross-functional partners see you as a reliable thought partner for high-impact decisions.