HEOR Analyst – Biostatistician

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).