Real World Biostatistician - RWE CMH experience

Job Responsibilities

• Design and execute real-world evidence (RWE) studies using EMR and claims data;
• Conducting 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

Required 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

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
• RWE CMH Experience

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