Health Economics Model Evaluation Expert

Create realistic economic evaluations from the research question through the final recommendation. Write reference answers that explain your methodological choices clearly to other economists.

• Rate AI-generated analyses for soundness, defensible assumptions, and clear reasoning.
• Spot analyses that could mislead payers or regulators, even when they seem plausible.
• Apply health economics and outcomes research judgment to costs, evidence, and health outcomes.

• Remote contractor work with ongoing projects and an asynchronous schedule.
• Commitment: 20 or more hours per week.
• Open to candidates in the countries listed for this role.
• Graduate degree such as an MS, MPH, or PhD in health economics, economics, public health, epidemiology, or a related quantitative field.
• At least three years of professional or research experience in health economics or outcomes research, plus hands-on experience building economic models.
• Clear written English and depth in cost-effectiveness modeling, budget impact, real-world evidence, or health technology assessment submissions.
• Helpful experience includes submissions for NICE, ICER, CADTH, PBAC, IQWiG, or AMCP; tools such as R, TreeAge, Excel, VBA, Stata, or SAS; and claims or electronic health record data such as MarketScan, Optum, IQVIA, Medicare, SEER-Medicare, or Flatiron.

Apply on OpenTrain with your resume, then complete the application on the hiring site.

AI training uses human examples and reviews to help improve how AI models respond. In this role, health economics expertise helps create evaluation examples and assess whether model analyses are sound.