Principal Statistical Programmer

Key Responsibilities

• Develop complex analysis datasets, specifications, and summary outputs (tables, listings, figures, and graphs) for inclusion in clinical study reports, regulatory submissions, and internal presentations.
• Create, modify, and maintain SAS programs that meet regulatory and company standards to ensure efficient programming, reporting, review, and traceability.
• Perform independent program review and validation, ensuring complete, accurate, and inspection-ready documentation in compliance with applicable regulations and internal procedures.
• Support ad hoc and planned analyses in collaboration with the designated statistician, including responses to data review questions.
• Partner with Clinical Data Management and Biostatistics to review CRFs, database specifications, edit checks, and data derivations as needed.
• Proactively identify programming risks, data issues, or efficiency opportunities and communicate them clearly to study team members.

Required Skills/Experience

• Bachelor’s degree in Statistics, Mathematics, Computer Science, or a related field with 5+ years of relevant statistical programming experience, or Master’s degree (or equivalent) with 3+ years of relevant statistical programming experience.
• Demonstrated experience performing statistical programming in a clinical trials environment (pharmaceutical and/or medical device).
• Strong hands-on experience with SAS programming for clinical trial data including SAS Base, SAS/STAT, and SAS Macros.
• Proven experience developing and validating: Analysis datasets, Tables, listings, and figures.
• Solid understanding of regulatory requirements and guidelines applicable to clinical research (e.g., GCP, ICH, FDA, ISO).
• Experience with CDISC standards (e.g., SDTM, ADaM).
• Experience supporting programming deliverables that are inspection-ready.
• Proficiency interfacing SAS outputs with common productivity tools (e.g., Microsoft Excel, Word, PowerPoint).
• Strong analytical, problem-solving, and organizational skills.
• High attention to detail and commitment to data quality.
• Clear written and verbal communication skills.
• Able to collaborate effectively with cross-functional stakeholders, including statisticians and data managers.
• Able to manage competing priorities in a fast-paced project environment.