Senior Specialist – Health Economics Modelling (HEOR)

Role Overview We are seeking a highly motivated HEOR professional to support evidence generation and market access initiatives. This role involves developing robust economic models, generating insights, and collaborating with cross-functional stakeholders to drive decision-making in healthcare. Key Responsibilities Design, develop, and maintain health economic models using advanced Excel techniques, including: Budget Impact Models (BIM) Cost-Effectiveness Models (CEM) Burden of Disease Models Build and validate decision-analytic models (Markov models, decision trees) to simulate disease pathways, treatment outcomes, and long-term impacts.

Conduct deterministic and probabilistic sensitivity analyses, scenario testing, and model validation to ensure accuracy and robustness. Interpret and synthesize clinical, epidemiological, and economic data (trial data, literature, real-world evidence) to populate models. Support health technology assessment (HTA) submissions and reimbursement dossiers across global markets.

Develop clear, client-ready deliverables such as technical reports, slide decks, and publications. Collaborate with cross-functional teams including Medical Affairs, Market Access, Commercial, and Data Science. Operational Excellence & Governance Ensure adherence to defined SLA timelines , quality standards, and delivery benchmarks.

Participate in model review cycles , validation checks, and audit readiness processes. Maintain documentation in line with best practices (e.g., ISPOR/SMDM guidelines). Track project progress, proactively flag risks, and ensure timely resolution of issues.

Contribute to process improvements, standardization, and knowledge-sharing initiatives. Required Qualifications Master’s degree (or higher) in Health Economics, Pharmacoeconomics, Public Health, Biostatistics, or related discipline. 4+ years of experience in health economic modelling and outcomes research. Strong expertise in decision-analytic modelling (Markov models, decision trees).

Advanced Excel skills (including complex formulas; VBA is an advantage). Good understanding of HTA frameworks, reimbursement landscapes, and payer requirements. Strong analytical thinking, attention to detail, and problem-solving ability.

Ability to manage multiple priorities in a fast-paced environment. Preferred Qualifications Experience with tools such as TreeAge, R, or Python for modelling or analysis. Exposure to real-world evidence (RWE) and systematic literature reviews (SLR).

Prior experience in consulting, life sciences, or pharmaceutical environments. Familiarity with global HTA bodies (e.g., NICE, CADTH, PBAC).