Role Description
We are seeking a biostatistician with strong experience in real-world data (RWD) with observational study design and safety study experience in addition to RWE CMH experience. This role will support evidence generation across multiple therapeutic areas, focusing on the design, analysis, and interpretation of observational studies using EMR and claims data to inform:
• Clinical development
• HEOR
• Regulatory strategy
• Market access
Key Responsibilities
• Design and execute real-world evidence (RWE) studies using EMR and claims data
• Conduct data specs, SAP, and protocol with key research objectives
• Develop and apply robust statistical methodologies, including:
• Causal inference methods (e.g., propensity score methods, weighting, matching; GLM or GLMM, MMRM; survival analysis; random forest)
• Trial emulation frameworks
• External control arm development and borrowing strategies
• Perform data analysis using healthcare coding systems (e.g., ICD, NDC)
• Conduct sample size estimation and power calculations for observational and hybrid study designs
• Collaborate cross-functionally with stakeholders across:
• HEOR
• Market Access
• Regulatory
• Clinical Development
• Translate complex analytical results into clear, actionable insights (e.g., PowerPoint or study report for decision-making)
• Support methodological innovation in RWE, including integration of machine learning approaches where appropriate
Qualifications
• M.S. or Ph.D. in Biostatistics, Statistics, Epidemiology, or related field
• ≥5 years of experience in RWD/RWE analytics (industry or equivalent)
• Strong experience with EMR and/or claims data
• Proficiency in healthcare coding systems (e.g., ICD, NDC)
• Programming expertise in at least one of: SAS, R, or Python
• Working knowledge with SQL logic and OMOP data structures
• Solid understanding of:
• Causal inference methods
• Observational study design
• Sample size and power considerations
• Some examples: Independently write cohort definitions in SQL logic; Debug data issues (e.g., time zero alignment, exposure gaps); Understand concept mapping (ICD ↔ SNOMED ↔ RxNorm); Translate statistical estimand → censoring rule and data extraction logic
Requirements
• RWE CMH Experience
Preferred Qualifications
• Ph.D. strongly preferred
• Experience in one or more therapeutic areas:
• Diabetes
• Cardiovascular disease
• Metabolic disorders
• Familiarity with:
• Trial emulation methodologies
• External control borrowing / hybrid designs
• Basic machine learning methods applied to RWD
• Demonstrated ability to work across multiple therapeutic areas (TAs) in a fast-paced environment
• Strong communication and stakeholder engagement skills
Core Competencies
• Analytical rigor and methodological depth
• Cross-functional collaboration
• Ability to operate with agility across diverse projects and therapeutic areas
• Clear and effective scientific communication
Additional Information
Tasks, duties, and responsibilities as listed in this job description are not exhaustive. The Company, at its sole discretion and with no prior notice, may assign other tasks, duties, and job responsibilities. Equivalent experience, skills, and/or education will also be considered so qualifications of incumbents may differ from those listed in the Job Description. The Company, at its sole discretion, will determine what constitutes as equivalent to the qualifications described above. Further, nothing contained herein should be construed to create an employment contract. Occasionally, required skills/experiences for jobs are expressed in brief terms. Any language contained herein is intended to fully comply with all obligations imposed by the legislation of each country in which it operates, including the implementation of the EU Equality Directive, in relation to the recruitment and employment of its employees. The Company is committed to compliance with the Americans with Disabilities Act, including the provision of reasonable accommodations, when appropriate, to assist employees or applicants to perform the essential functions of the job.