Senior Specialist – Health Economics Modelling; HEOR

Position: 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  Tree Age, 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).