Back to Job Search

Manager, Statistical Programming

  • Location: Princeton
  • Salary: US$140000.00 - US$160000.00 per annum per year
  • Job Type:Permanent

Posted 24 days ago

  • Sector: Life Sciences
  • Contact: Alicia Licht
  • Expiry Date: 02 October 2022
  • Job Ref: JN -082022-473116

Manager of Statistical Programming needed for growing team in the Princeton, NJ area. Ideally this persion will be onsite part of the time, but can consider a remote arrangement w/occassional travel


  • Manages assignments and programming on multiple projects.
  • Participates in the development of and ensures compliance to Standard Operating Procedures (SOPs), policies, and guidelines.
  • Remains informed of new developments in programming that are relevant to the industry and contributes to the innovation of new reporting systems.
  • Establishes and implements programming standards and complies with regulatory requirements among project team members and across studies.
  • Develops standard macros and/or tools in SAS for data analysis and reporting.
  • Assists with statistical quality assurance review.
  • Reviews deliverables before transfer to either internal or external clients.
  • Ensures that SAS programs developed for specific protocols are effectively translatable to other protocols (reusable code).
  • Performs the work of statistical programming services across sites to achieve quality, timely, and cost-effective study deliverables.
  • Responsible for hands-on programming for ADaM datasets and TLF deliverables.


  • MS degree in statistics or computing-related field or equivalent training required
  • A minimum of 6 years of industry or CRO experience required.
  • Experience leading SAS programming projects in the pharmaceutical industry, demonstrated by the ability to independently act as the point of contact for statistical programming over all phases of clinical trials.
  • Proficient in industry standards, medical terminology, and clinical trial methodologies.
  • Possesses project management skills within the Statistical Programming function.
  • Regulatory (FDA and EMA) submission experience (including CDISC preparation) is highly preferred