Senior Data Analyst, Quality

Collaboration Prepare clear written narrative summaries of findings for both technical and non-technical audiences. Develop and deliver executive-level presentations that translate complex analytical results into actionable insights for clinical, operational, and leadership stakeholders. Engage proactively with clinical teams to understand measure intent and ensure analytical outputs align with real-world care delivery context. Participate in team meetings, cross-functional working groups, and contribute to broader organizational and strategic initiatives. EDUCATION Bachelor's degree in Statistics, Biostatistics, Public Health, Health Informatics, Computer Science, Mathematics, or a closely related quantitative field. REQUIRED QUALIFICATIONS 4+ years of experience in healthcare data analytics, with a demonstrated track record managing large, complex healthcare databases. Proficiency in SQL, including complex query writing, aggregation, and performance optimization across large relational datasets. Hands-on experience with healthcare claims data across Commercial, Medicare, and Medicaid payer types. Experience with VRDC, CMS data assets, or other government-sourced Medicare/Medicaid datasets. Deep familiarity with US healthcare coding systems: HCPCS, CPT, ICD-10, and DRG. Demonstrated experience developing, validating, and deploying statistical models for healthcare analytics. Excellent written and verbal communication skills; proven ability to present analytical findings to both clinical and non-technical audiences. Advanced analytical, organizational, and problem-solving skills with high personal accountability for work quality. Familiarity with HIPAA and data governance standards applicable to healthcare data environments. PREFERRED QUALIFICATIONS Experience working in a Databricks environment, including notebook-based workflows and delta tables. Proficiency in Python, R, and/or SAS for statistical analysis and data processing. Prior exposure to quality measure development frameworks (e.g., NQF, HEDIS, or CMS measure specifications). Familiarity with ETL frameworks and enterprise data warehouse (EDW) environments.