Description
Develop, validate, and maintain statistical programming to implement biostatistical methods and generate compliant datasets, tables, listings, and figures for life science studies.
- • Translate study protocols and statistical analysis plans into programming specifications and TLF shells.
- • Write efficient, well-documented SAS, R, or Python code to analyze clinical and life science data.
- • Build and maintain SDTM and ADaM analysis datasets with complete traceability.
- • Program and quality-control tables, listings, and figures for reports and submissions.
- • Develop and validate reusable macros, functions, and code libraries.
- • Perform independent validation or double programming of datasets and outputs.
- • Create and maintain metadata, define.xml, and reviewer guides for regulatory packages.
- • Import, clean, transform, and merge data from multiple sources and formats.
- • Implement statistical models and algorithms as specified by biostatisticians.
- • Conduct data checks and create listings to monitor data quality and protocol compliance.
- • Document programming processes, assumptions, and results per SOPs and GxP.
- • Estimate programming effort, plan timelines, and track deliverables.
- • Collaborate with biostatisticians, data managers, and clinicians to resolve data and specification issues.
- • Review protocols and SAPs to understand endpoints, derivations, and analysis methods.
- • Automate workflows and reporting pipelines; manage code under version control.
- • Optimize code performance and resource usage for large datasets.
- • Support interim analyses, data monitoring committees, and clinical study reports.
- • Prepare analysis outputs and datasets for submission to regulatory agencies and clients.
- • Implement simulations or resampling analyses per specifications.
- • Provide programming consultation and support to study teams and stakeholders.
- • Train or mentor junior programmers and conduct code reviews.
- • Keep current with CDISC standards, regulatory guidance, and programming best practices.
- • Ensure compliance with ICH, GCP, and data privacy requirements in programming deliverables.
- • Address ad hoc data requests and produce exploratory analyses or visualizations.
- • Maintain reproducible research environments and audit-ready programming archives.
- • Participate in audits and inspections and respond to programming-related findings.
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Last reviewed: Jan 2026
