Thank you for considering the Medical Data Analyst position at Reveal Health Tech. We are a Series A–stage IT startup based in the US and India, delivering technology-driven solutions for the healthcare and life sciences industry as we scale toward our next phase of growth.
Requirements
About the Role
We’re looking for a Medical Data Analyst who can turn messy healthcare data into crisp, decision-ready insights. You’ll build end-to-end analytics solutions, support value-based care initiatives, and partner closely with provider groups, specialty groups, and payers to surface opportunities that improve outcomes, margin performance, and total cost of care. You’ll also play a key role in analyzing actuarial and contract performance dynamics- evaluating utilization trends, PMPM/TCOC, and contract benchmarks to ensure programs are financially aligned and sustainable.
What You’ll Do
- Build analytics products: Own the full Power BI lifecycle—data modeling, DAX, visuals, RLS, deployment, and documentation.
- Enable value-based care (VBC): Define and track measures (e.g., readmissions, avoidable ER/IP, adherence, risk acuity, PMPM/TCOC), attribution logic, and cohorting.
- Actuarial & contract performance analysis: Support actuarial-oriented analyses including PMPM + risk-adjusted cost modeling, benchmarking, savings reconciliation, trend analysis, and scenario modeling.
- Data wrangling & QA: Ingest, clean, validate, and reconcile claims, eligibility, EMR, and care-management data.
- Performance tracking: Build scorecards and drill-downs for executives, clinicians, care teams, actuarial partners, and payer counterparts.
- Operationalize insights: Create recurring datasets, alerts, and self-service dashboards; document metric definitions, lineage, and reconciliation rules.
- Governance & compliance: Uphold HIPAA/privacy requirements and contribute to data quality standards.
- Ad-hoc analysis: Run cohort analyses, payer/provider comparisons, utilization analysis, risk-adjusted benchmarking, leakage patterns, and trend studies.
Minimum Qualifications
- 3+ years in healthcare analytics, actuarial services, population health, or payer/provider performance.
- Strong Power BI (DAX, Power Query/M, data modeling, RLS).
- Solid SQL (CTEs, window functions, performance tuning) and comfort with large datasets.
- Hands-on with claims/eligibility (837/835 concepts, CPT/HCPCS/ICD-10, NPI, taxonomy), EMR extracts, and payer/provider data nuances.
- Experience collaborating with provider groups and payers—requirements gathering, walkthroughs, and iteration.
- Understanding of value-based care concepts (TCOC, PMPM, savings reconciliation, attribution, risk adjustment, quality measures).
- Ability to convert ambiguous analytic questions into concrete business metrics with documented methodologies.
Preferred Qualifications
- Experience with actuarial or contract modeling, shared savings, capitation, bundles, or delegated risk arrangements.
- Experience in cardiology/specialty care, care-management, or remote patient monitoring.
- Python or R for data prep/statistics; exposure to dbt or ETL tooling.
- Cloud data platforms (Azure Synapse/SQL, Databricks, Snowflake, or Redshift).
- Familiarity with HEDIS/STARs, RAF/HCC models, quality specifications, and performance reporting.
- Data governance: lineage, cataloging, metric definitions, reconciliation rules.
Tech Stack You May Use Here
- BI: Power BI (Service, Desktop, Deployment Pipelines)
- Data: SQL Server/Azure SQL/Synapse (or similar), Power Query/M, APIs/flat files
- Scripting (nice-to-have): Python (pandas), dbt
- DevOps: Git, CI/CD for BI artifacts, Workspaces, RLS/ALS
