Director HTA Statistics – RWE Methods

Jobtailor; Beerse; Sur place; EUR 90 000 - 150 000; Plein temps

Résumé du poste

Jobtailor in Belgium seeks a senior statistician to lead payer/HTA evidence generation and RWE program design. You will shape strategy by synthesizing external case studies and ensuring governance across projects.

You will design advanced analyses, train teams, and contribute to analytics platforms, leveraging SAS and R to advance market access and launch strategies for key assets.

Qualifications

• Postgraduate degree in Biostatistics, Epidemiology, Data Science, Health Economics, or related field.
• Minimum 8 years of relevant experience in pharmaceutical, biotech, or consulting environments.
• Demonstrated experience in advanced statistical methodologies relevant for payer/HTA evidence generation including indirect treatment comparisons and RWE.
• Deep expertise in clinical trial design and secondary data sources (claims, EMR, registries, surveys).
• Advanced knowledge of statistical methodologies for market access, including indirect treatment comparisons and causal inference approaches.
• Strong understanding of regulatory and payer/HTA frameworks and their applications.

Responsabilités

• Maintain deep expertise in evolving methodologies including regulatory, payer/HTA, and guideline/formulary evidentiary requirements.
• Review, synthesize, and disseminate external case studies and precedents to shape internal strategy and analyses.
• Act as key reviewer for the Global RWE Methods Review Board, ensuring governance and methodological consistency across programs.
• Lead the design of advanced study designs and statistical analyses aligned with payer/HTA expectations.
• Provide contributions to capability building, including training for the team and development of coding libraries and AI/ML analytics platforms.

Connaissances

Advanced statistics

Payer/HTA knowledge

Study design

Training initiatives

Analytical platforms

Formation

MSc/PhD in Biostatistics, Epidemiology, Data Science, Health Economics, or related field

Outils

SAS

R

Description du poste

Responsibilities

• Maintain deep expertise in evolving methodologies, including proactive awareness of regulatory, payer/HTA, and guideline/formulary evidentiary requirements.
• Review, synthesize, and disseminate external case studies and precedents to shape internal strategy and analyses.
• Act as key reviewer for the Global RWE Methods Review Board, ensuring robust governance and methodological consistency across programs.
• Lead the design of advanced study designs and statistical analyses aligned with payer/HTA expectations (e.g., indirect treatment comparisons, causal inference methods, surrogate endpoint validations, etc.) to support market access and launch strategies for key assets.
• Provide key contributions to capability building, including training for team on payer/HTA requirements and new methodologies and also in the development of coding libraries and AI/ML advanced analytics scaling and platforms, etc.

Requirements

• Postgraduate degree (MSc, PhD) in Biostatistics, Epidemiology, Data Science, Health Economics, or related field
• Minimum 8 years of relevant experience in pharmaceutical, biotech, or consulting environments
• Demonstrated experience in advanced statistical methodologies relevant for payer/HTA evidence generation including indirect treatment comparisons and RWE.
• Deep expertise in clinical trial design and the strengths and limitations of secondary data sources (claims, EMR, registries, surveys)
• Advanced knowledge of statistical methodologies for market access, including indirect treatment comparisons and causal inference approaches
• Strong understanding of methodological standards, regulatory and payer/HTA frameworks and their application to evidence generation.
• Hands‑on proficiency in statistical programming (SAS, R; desirable)

Core Competencies

Expertise in advanced statistical methodologies and clinical trial design, with a strong focus on payer/HTA requirements and evidence generation. Proficient in statistical programming and capable of leading training initiatives and developing analytical platforms.