Contact: Neisha Camacho/Terra Parsons - teamnt@penfieldsearch.com
No 3rd party candidates
We are seeking a highly experienced Statistical Programmer to lead programming activities across global clinical studies. This role operates beyond executional programming, with responsibility for oversight of CRO deliverables, validation of outputs, and end-to-end accountability for statistical programming packages.
Key Responsibilities
- Lead statistical programming activities across global studies
- Serve as primary programming lead in collaboration with Biostatistics
- Develop, review, and validate SDTM and ADaM datasets in accordance with CDISC standards
- Review specifications and proactively challenge inconsistencies in protocols, SAPs, and dataset definitions
- Validate program outputs and ensure accuracy, quality, and regulatory compliance
- Provide oversight and guidance to CRO partners, consolidating and communicating feedback effectively
- Manage timelines, delivery packages, and milestone commitments
Contribute to continuous improvement of programming processes and standards
Core Requirements
- Strong expertise in CDISC standards, including ADaM and SDTM
- Demonstrated experience reviewing specs and ensuring high-quality, submission-ready deliverables
- Working experience in LSAF environment
- Experience validating CRO programming deliverables
- Ability to operate with increased performance accountability and ownership
- Strong CRO-facing communication and collaboration skills
- Proven ability to manage multiple global studies simultaneously
Additional RequirementsÂ
- Practical experience with multiple imputation (MI), particularly under Missing at Random (MAR) assumptions
- Familiarity with the estimands framework (ICH E9 R1) and managing intercurrent events (ICEs) within ADaM domains using various strategies
Qualifications
- Bachelor’s or Master’s degree in Statistics, Mathematics, Computer Science, or related field
- 5+ years of SAS programming experience within pharmaceutical/biotech
- Strong understanding of statistical methods used in clinical trial analysis
- Knowledge of Good Programming Practices and GCP
- Preferred: Experience with R programming