About this role
In this pivotal role, you will leverage your expertise in revenue cycle management (RCM) analytics and decision-support to enhance the capabilities of next-generation AI systems. Your leadership will be instrumental in evaluating AI tools that aim to transform revenue cycle intelligence and financial decision-making, providing actionable insights across the entire revenue cycle.
Key Responsibilities- Lead revenue cycle analytics, reporting, and decision-support functions to drive data-driven performance improvement across RCM operations.
- Evaluate AI-generated revenue cycle analytics outputs, KPI dashboards, and financial modeling recommendations for accuracy and completeness.
- Develop and maintain revenue cycle reporting frameworks covering patient access, coding, billing, denials, accounts receivable, and collections performance.
- Build and interpret dashboards, scorecards, and trend analyses to support operational and executive decision-making.
- Conduct root cause analyses of revenue cycle performance variances and develop data-driven improvement recommendations.
- Collaborate with finance, IT, and operational revenue cycle teams to align analytics infrastructure with strategic priorities.
- Manage RCM data governance, including data definitions, data quality standards, and reporting consistency.
- Support revenue cycle forecasting, budget modeling, and net revenue realization analysis.
- Annotate AI outputs and provide structured analytical feedback to support AI training datasets.
- 5+ years of experience in revenue cycle analytics, RCM reporting, or healthcare financial decision-support, with at least 2 years in a leadership role.
- Deep knowledge of revenue cycle KPIs and financial metrics across patient access, coding, billing, denials, and collections domains.
- Proficiency with healthcare analytics platforms, BI tools (Tableau, Power BI, or equivalent), and SQL-based data analysis.
- Experience with EHR-integrated analytics platforms and RCM reporting systems.
- Strong financial modeling and data interpretation skills with the ability to translate complex data into actionable recommendations.
- Exceptional written and verbal English communication skills.
- High attention to detail with the ability to identify data quality issues and analytical errors in AI-generated outputs.
- HFMA CRCR, CHFP, or healthcare analytics certification.
- Experience with predictive analytics, revenue cycle forecasting, and net revenue modeling.
- Background in health system, large physician enterprise, or RCM outsourcing analytics operations.
- Familiarity with AI tools and comfort evaluating AI-generated analytics content.
- Experience implementing enterprise-wide revenue cycle analytics infrastructure or BI platform migrations.
- Contribute to the development of frontier AI systems in healthcare.
- Collaborate with a world-class AI research organization.
- Gain exposure to cutting-edge AI workflows in revenue cycle analytics and decision-support.
- Opportunity to work on high-impact projects shaping the future of healthcare AI.