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