Health Economics and Outcomes Research Scientist

Health Economics and Outcomes Research (HEOR) Scientist

Background:

Our client is seeking a Health Economics & Outcomes Research (HEOR) Scientist to support the Medical Affairs modeling group in advancing the economic and clinical evidence base for an in-market diagnostic product. This position will focus on developing and executing health economic models, specifically microsimulation and cost-effectiveness models built in Python, to demonstrate the product’s value to patients, providers, payers, and policymakers. The role requires strong quantitative and analytical skills, familiarity with health economic modeling methods, and the ability to work collaboratively in a fast-paced, research-driven environment. This is a fully remote, full-time position.

Key Responsibilities:

• Develop, refine, and execute microsimulation and cost-effectiveness models to evaluate health and economic outcomes.
• Perform large-scale data analyses and experimentation to inform model inputs and assumptions.
• Support health outcomes and real-world evidence (RWE) projects by integrating clinical, economic, and epidemiological data.
• Apply Python programming to develop reproducible, data-driven models while leveraging cloud computing platforms such as AWS or Databricks.
• Conduct probabilistic sensitivity analyses, scenario testing, and model validation to ensure methodological rigor.
• Communicate findings effectively to internal and external stakeholders through reports, visualizations, and presentations.
• Collaborate with cross-functional partners in Medical, Market Access, and Regulatory Affairs to ensure alignment on model objectives and outcomes.
• Document modeling approaches, assumptions, and methodologies in a clear and transparent manner suitable for publication or submission.
• Adhere to company policies, quality management procedures, and data security standards.

Qualifications:

• Graduate degree in Health Economics, Operations Research, Epidemiology, Public Health, Mathematical Modeling, or a related quantitative field.
• Proven experience developing or supporting health economic and outcomes research models.
• Proficiency in Python, including data manipulation, statistical modeling, and visualization.
• Familiarity with cloud-based computing environments such as AWS or Databricks.
• Understanding of cost-effectiveness analysis, health technology assessment, and economic evaluation frameworks.
• Ability to translate complex analytical findings into actionable insights for diverse audiences.
• Strong written and verbal communication skills with demonstrated attention to detail.
• Ability to manage multiple projects independently and deliver results within defined timelines.
• Record of research publications or experience in scientific manuscript development preferred.