Core Skills & Competencies
Health Economics & Outcomes Research: Deep understanding of health
economic modeling, outcomes research, healthcare resource utilization, real-
world evidence, cost-of-care analysis, comparative effectiveness, and value
assessment methodologies.
Economic Modeling: Demonstrated ability to develop and critically evaluate
budget impact, cost-effectiveness, cost-utility, ROI, decision-tree, Markov/state-
transition, and related economic models.
Payer & Market Access Strategy: Strong understanding of payer evidence
requirements and the ability to translate clinical and economic evidence into
compelling value propositions supporting reimbursement, coverage, and
adoption.
Evidence Generation & Clinical Strategy: Ability to integrate HEOR endpoints
and evidence requirements into clinical development and real-world research
programs, anticipating future reimbursement and HTA needs.
Scientific Communication & Publication: Strong scientific writing and
communication skills with experience translating complex analyses into
manuscripts, abstracts, presentations, value dossiers, payer materials, and
executive-level communications.
Cross-Functional Leadership: Proven ability to work across clinical, medical,
statistical, market access, commercial, and business functions and to influence
evidence strategy in a matrixed organization.
Global Perspective: Understanding of U.S. and international reimbursement
environments and major HTA frameworks, including ICER, NICE, CADTH,
PBAC, IQWiG, and Japanese reimbursement processes.
Advanced degree (PhD, PharmD, MD, DrPH, or Master's degree) in Health
Economics, Outcomes Research, Epidemiology, Public Health, Biostatistics,
Pharmacy, Health Services Research, or a related discipline.
5–10+ years of HEOR experience within biotechnology, pharmaceuticals,
diagnostics, medical devices, consulting, academia, or a related healthcare
environment.
Demonstrated experience developing and applying health economic models and
conducting outcomes research using clinical-trial and/or real-world datasets.
Experience supporting payer evidence generation, reimbursement strategy, value
dossiers, market access initiatives, and scientific publications.
Experience with precision medicine, molecular diagnostics, companion
diagnostics, ctDNA, molecular residual disease (MRD), donor-derived cell-free
DNA (dd-cfDNA), next-generation sequencing, biomarker-guided treatment
strategies, or oncology diagnostics is highly desirable.
Familiarity with advanced economic and analytical tools such as Microsoft Excel,
TreeAge Pro, R, SAS, STATA, Python, SQL, Tableau/Power BI, and statistical
analysis software is preferred.