Senior Healthcare Data Analyst

Role Description

This role leads advanced analytics supporting Medicare and Risk Adjustment programs, with a focus on driving accurate risk score capture (RAF), improving performance against CMS benchmarks, and supporting enterprise risk‑adjustment strategies. The analyst partners closely with clinical, coding, finance, operations, and compliance stakeholders to translate complex Medicare data into actionable insights.

Key Responsibilities

• Lead analytical initiatives supporting Medicare and CMS Risk Adjustment programs
• Analyze large healthcare datasets (claims, encounters, enrollment, chart reviews, and clinical data) to:
  • Identify RAF optimization opportunities
  • Monitor coding accuracy and completeness
  • Assess financial and operational impact of risk score changes
• Develop and maintain SQL‑based data pipelines and analytic models in large data warehouse environments
• Produce executive‑level reporting and dashboards addressing:
  • HCC performance
  • Coding gap closure
  • Suspect and recapture outcomes
  • Provider and member impact
• Translate CMS regulations, risk adjustment models, and technical findings into clear business insights
• Partner with coding, clinical, compliance, and operational leaders to support risk‑adjustment initiatives
• Serve as a subject matter expert on Medicare data, metrics, and CMS standards
• Lead or support analytic projects end‑to‑end, including scope definition, analysis, and stakeholder delivery

Qualifications

• Bachelor’s degree in Statistics, Mathematics, Economics, Computer Science, Actuarial Science, Healthcare, or a related field
• 3+ years advanced SQL expertise in enterprise data warehouse or big‑data environments
• 3+ years experience with healthcare analytics, including large, complex datasets
• Experience developing reports and visualizations using tools such as Tableau, Power BI, or Microsoft Access
• Strong understanding of relational databases and healthcare data structures (claims, encounters, member, provider)
• Demonstrated ability to clearly communicate statistical and technical results to non‑technical audiences
• Proven analytical problem‑solving and critical‑thinking skills
• Experience collaborating across multidisciplinary healthcare teams

Preferred Qualifications

• Direct experience with Medicare and Risk Adjustment, including:
  • CMS‑HCC models
  • RAF calculations
  • Coding gap or suspect analysis
• Master’s degree in a quantitative or healthcare‑related discipline
• Experience in health plan or provider environments
• Background in:
  • Multivariate statistical modeling
  • Health economics or outcomes research
  • Predictive modeling or data mining
• Familiarity with CMS regulations, submission processes, and audit concepts
• Prior project leadership or team lead experience
• Strong understanding of healthcare data standards, quality measures, and compliance considerations

Education

• Bachelor's degree or equivalent work experience

Anticipated Weekly Hours

• 40

Time Type

• Full time

Pay Range

The typical pay range for this role is: $46,988.00 - $112,200.00. This pay range represents the base hourly rate or base annual full-time salary for all positions in the job grade within which this position falls. The actual base salary offer will depend on a variety of factors including experience, education, geography and other relevant factors. This position is eligible for a CVS Health bonus, commission or short-term incentive program in addition to the base pay range listed above.

Benefits

• Comprehensive benefits package designed to support the physical, emotional, and financial well‑being of colleagues and their families
• Medical, dental, and vision coverage
• Paid time off
• Retirement savings options
• Wellness programs and other resources, based on eligibility

Application Information

We anticipate the application window for this opening will close on: 06/02/2026. Qualified applicants with arrest or conviction records will be considered for employment in accordance with all federal, state and local laws.