into trusted, actionable insights that improve outcomes and reduce medical waste. You will work
with clinical, finance, operations, product, and technology partners to deliver analytics that
support better decisions.
What You'll Do
* Build and maintain data models and semantic layers for analytics use cases under team guidance.
* Support end-to-end insight work: problem framing, analysis, visualization, and communication.
* Partner with Product, Clinical Analytics, Medical Economics, Finance, and Operations on team
priorities.
* Use AI-enabled workflows (for example, AI-assisted analysis and documentation) to improve
productivity
and insight quality while following team standards.
* Create intuitive dashboards and reporting experiences for business and clinical stakeholders.
* Contribute to data quality, documentation, and analytics standards across core reporting assets.
* Apply hypothesis-driven analysis to help identify opportunities to improve patient outcomes and reduce
avoidable cost.
* Learn from senior teammates and share knowledge through collaboration and documentation.
Qualifications
* 2+ years of experience in analytics engineering, BI, or data-focused analytics roles.
* Strong SQL proficiency; exposure to cloud data warehouses (Snowflake preferred).
* Familiarity 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 business questions into clear analytical plans with support from teammates.
* Clear 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 willingness to learn and take
ownership.
What Success Looks Like
* Stakeholders use your insights to support day-to-day and tactical decisions.
* Analytics outputs are timely, accurate, and aligned to defined business questions.
* Data assets you build are documented and reusable by the team.
* Cross-functional partners

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