Manager Statistical Programming
Manager, Statistical Programming
Location: New Jersey (Hybrid - 3 days onsite)
Salary: $110,000-$140,000 + bonus + benefits
Overview
We're currently partnered with a growing, mid-sized biotechnology organization is seeking a Manager, Statistical Programming to support clinical development programs and lead statistical programming activities across multiple studies. This individual will play a key role in delivering high-quality programming outputs for regulatory submissions while acting as a technical expert within the biometrics function.
Key Responsibilities
- Serve as the technical lead and project manager for statistical programming deliverables across multiple clinical studies
- Oversee the development and validation of analysis datasets, tables, listings, and figures (TLGs) to support regulatory submissions and publications
- Collaborate cross-functionally with Biostatistics, Data Management, Clinical Operations, and Medical Writing to ensure alignment on study deliverables and timelines
- Represent Statistical Programming at study team and clinical development meetings
- Review key study documents including SAPs, CRFs, data management plans, and database specifications
- Develop and maintain SAS programs, macros, and utilities to support study- and product-level analyses
- Provide guidance on complex programming tasks and contribute to internal standards, SOPs, and best practices
- Interface with external CROs and vendors, ensuring quality and timely delivery of outsourced programming work
Qualifications
- Bachelor's degree (or higher) in Statistics, Computer Science, Mathematics, or related discipline
- 5+ years of experience in statistical programming within a clinical development environment
- Strong expertise in SAS programming, with working knowledge of CDISC standards (SDTM, ADaM)
- Experience generating outputs to support regulatory submissions (FDA/EMA)
- Familiarity with R and/or Python is a plus
- Proven ability to work in a cross-functional, fast-paced environment and manage competing priorities
- Understanding of the drug development lifecycle across various phases
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