Medical Economics Analyst – Health Plan

Posted 2026-05-05
Remote, USA Full-time Immediate Start
    Job Description:
  • Analyze complex medical claims, pharmacy data, and other healthcare data sets to identify emerging cost and utilization trends, patterns, and outliers.
  • Develop financial models to evaluate the financial impact of new clinical programs, new initiatives, and value-based agreements.
  • Identify opportunities for medical cost reduction, quantify potential savings, and measure the return on investment (ROI) of implemented initiatives.
  • Create clear, concise reports, dashboards, and presentations using data visualization tools to communicate complex findings and actionable insights to a variety of stakeholders, including senior management and clinical departments.
  • Work closely with accounting, actuarial, underwriting, clinical, health services delivery and network management teams to provide analytical support for decision-making and strategic planning, such as informing payer negotiations and risk adjustment strategies.
  • Ensure the accuracy and integrity of data used in analyses, and prepare well-organized project documentation including methodologies and key decision points.
  • Respond to ad-hoc data analysis requests from various departments, providing timely intelligence related to specific business problems.
    Requirements:
  • Bachelor’s degree in Economics, Statistics, Finance, Public Health, Mathematics, Actuarial Science, Data Analytics or related quantitative discipline required.
  • 1-3 years of progressive analytical experience in a healthcare setting (health insurance, managed care, or health system) is required.
  • Knowledge of STARs and Risk Adjustment preferred.
  • Strong analytical, problem-solving, critical thinking, and communication skills are vital for success in this role.
  • Proficiency in SQL for data extraction and manipulation is a must.
  • Advanced Microsoft Excel skills, including pivot tables and complex formulas, are essential.
  • Experience with data visualization tools like Tableau or Power BI is highly valued.
  • Familiarity with statistical tools such as SAS, R, or Python is often a plus.

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