Principal Statistical Programmer
mcraDurham (NC)
About the role
Principal Statistical Programmer We are seeking a Principal Statistical Programmer to provide full end-to-end statistical programming support across clinical development programs. This role requires deep technical expertise, leadership, and hands-on delivery, covering SDTM, ADaM, TLF development, and regulatory submission support. The Principal Statistical Programmer will serve as a subject matter expert, ensure high-quality deliverables, and contribute to programming standards and best practices.
Key Responsibilities:
Provide end-to-end statistical programming support for clinical studies from study setup through submission
Lead and perform development and validation of:
- SDTM datasetsADaM datasets
- Tables, Listings, and Figures (TLFs)
- Ensure all deliverables are compliant with CDISC standards and regulatory requirements
- Support regulatory submissions (e.g., FDA, EMA), including define.xml, submission-ready datasets, and reviewer's guides
- Serve as a Principal-level programmer, providing technical leadership and guidance to other programmers as needed
- Contribute to and help maintain programming standards, macros, and validation processes
- Review and approve programming deliverables to ensure accuracy, consistency, and quality
- Collaborate closely with Biostatistics, Data Management, Clinical Operations, and Regulatory teams
- Proactively identify risks and propose efficient, compliant solutions within timelines
Required Qualifications:
Bachelor's or Master's degree in Statistics, Mathematics, Computer Science, Life Sciences, or related field
Extensive experience as a statistical programmer, with demonstrated Principal-level responsibilities
Strong hands-on experience with:
- SDTM and ADaM dataset developmentTLF programming
- Regulatory submission deliverables
- Expert proficiency in base SAS and Advanced SAS with good hands on SAS MacrosIn-depth knowledge of CDISC standards, regulatory guidelines, and submission requirements
- Proven ability to manage complex studies independently from start to finish
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