Biostatistical Analyst responsible for leading statistical analyses and supporting data product development at Elevance Health. Collaborates with scientific teams to ensure adherence to project commitments while enhancing flexible work culture.
Responsibilities
Develop statistical subject matter expertise of the research data and integrated environment
Lead and support statistical analysis with application of research methods in emerging real-world data sources and clinical research
Assist in reviewing and advising on data management activities (e.g., database/cohort identification, analytic file development, case report form (CRF) programming, validation checks, data issues resolutions)
Support development of statistical content for study documentation (e.g., protocols, statistical analysis plans), reports, publications and regulatory submissions
Perform execution of analytic methodology, including writing programming specifications, developing programs to perform statistical analysis, creating Tables, Listings and Figures (TLFs), and performing quality control of programs and ensuring integrity of analysis
Formulate ideas for new research studies and projects and contribute analytic insight to the writing of research proposals
Articulate methods, process, progress and results to internal and external stakeholders
Collaborate with the Scientific and Project Management teams to ensure adherence to scope, schedule, and budget commitments
Requirements
Requires a MS degree in Statistics or Biostatistics or a closely allied field with substantial statistical preparation
Advanced SAS and/or R programming, including macros/functions and reusable, auditable pipelines
Experience working in cloud-based analytics environments and large-scale data platforms (e.g., Snowflake, AWS)
Experience in commercial analytics for Life Sciences companies or equivalent consulting experience
Creation of high-quality Tables, Listings, and Figures (TLFs) with strong quality control and validation practices
Strong data provenance, data quality assessment, and validation expertise
Familiarity with version control, reproducible research principles, and clean, auditable code development
Hands-on experience with real-world data sources, including claims, EHR, registry, linked, and patient-level integrated data
Expertise in data linkage, cohort construction, and phenotype definition in complex, incomplete data
Understanding of healthcare coding systems (ICD, CPT, HCPCS, NDC, LOINC)
Awareness of real-world data (RWD) regulatory and evidentiary standards (e.g., FDA, HTA relevance)
Ability to translate statistical methodologies into practical analyses, including survival analysis, propensity scores, causal inference, and experimental design
Ability to align analyses with client, market, and product needs
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