GD Resources

Medicaid Economics Data Analyst

GD Resources

full-time

Posted on:

Location Type: Remote

Location: United States

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Salary

💰 $85,000 - $95,000 per year

Tech Stack

About the role

  • Analyze Medicare, Medicaid, and Marketplace data to support medical cost, utilization, and reimbursement insights
  • Develop and maintain complex SQL queries to extract, validate, and analyze large datasets
  • Perform financial and medical cost analyses related to payment and reimbursement methodologies (DRG, APC, EAPG)
  • Build and maintain Power BI dashboards using DAX and Power Pivot to track KPIs, MLR, and QAI initiatives
  • Create advanced Excel models using Pivot Tables, Power Query, nested formulas, and lookups to support financial modeling
  • Collaborate with Medical Economics, Actuarial, Finance, and other cross-functional teams
  • Support evaluation of Quality & Affordability Initiatives (QAI) and Medical Loss Ratio (MLR) performance
  • Ensure data accuracy through validation, reconciliation, and documentation

Requirements

  • Bachelor’s degree in business, economics, statistics, mathematics, actuarial science, public health, health informatics, healthcare administration, finance, or related field
  • Equivalent experience considered
  • 4+ years of experience working with large datasets, data management, and analytics OR 2+ years of IT/data-focused experience with healthcare exposure
  • Strong experience in Managed Care / Medical Economics analytics
  • Demonstrated knowledge of payment and reimbursement methodologies (DRG, APC, EAPG)
  • Advanced SQL skills (complex SELECTs, multiple JOINs, subqueries)
  • Advanced Excel skills (Pivot Tables, Power Query, VLOOKUP/XLOOKUP, financial modeling)
  • Power BI experience, including DAX and Power Pivot
Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools
SQLDAXPower PivotExcelPivot TablesPower Queryfinancial modelingdata analysisdata validationdata reconciliation
Soft Skills
collaborationcommunicationanalytical thinkingproblem-solvingattention to detail