This role requires candidates who are currently authorized to work in the U.S. without sponsorship, and C2C arrangements are not accepted. This role is remote.
Position Overview
We are seeking a HEOR Analyst - Biostatistician to provide analytical and statistical programming support within a Health Economics and Outcomes Research (HEOR) function.
This role operates as an integrated member of a cross-functional HEOR team and supports multiple concurrent initiatives across therapeutic areas using licensed real-world data assets. Work assignments may evolve based on business priorities.
Key Responsibilities
Real-World Data Analysis Support
• Conduct data queries and statistical analyses using licensed real-world data sources (e.g., claims, EHR/EMR, registries).
• Support ongoing HEOR initiatives across product portfolios and development-stage therapeutic areas.
• Analyze real-world populations to evaluate:
• Disease prevalence and incidence
• Disease burden and progression
• Healthcare resource utilization (HRU)
• Treatment patterns
Statistical Programming & Validation
• Develop and implement efficient SAS programs in support of HEOR analyses.
• Assist with development of study protocols and statistical analysis plans (SAPs).
• Perform quality control (QC) checks of:
• Own SAS programs
• Output produced by other programmers
• Ensure accuracy, reproducibility, and compliance with departmental standards.
Analytic Infrastructure & Standards
• Contribute to programming libraries and analytic tool development, including:
• Reusable macros
• Programming templates
• Standardized analytic utilities
• Track and archive projects according to established departmental standards.
• Maintain documentation supporting transparency and reproducibility of analyses.
Technical Expertise & Continuous Development
• Maintain current knowledge of:
• Medical coding systems (ICD, CPT, HCPCS, NDC, etc.)
• Large healthcare databases and real-world data assets
• Continuously develop statistical programming capabilities and methodological knowledge.
• Support consistent analytic practices across the HEOR function.
Minimum Qualifications
• Bachelor's degree in Computer Science, Statistics, Mathematics, or related field with strong statistical content.
• 3+ years of statistical programming or HEOR/real-world evidence experience.
• Advanced proficiency in SAS.
• Experience working with large healthcare datasets (claims, EHR, registry data).
• Strong understanding of observational study methodology.
Preferred Qualifications
• Master's degree in Epidemiology, Public Health, Biostatistics, or related quantitative discipline.
• Prior experience supporting HEOR or real-world evidence functions in pharmaceutical or biotech environments.
• Experience contributing to publications or abstracts.
• Familiarity with additional statistical programming languages (e.g., R, Python).