Principal Biostatistical Programmer

Premier Research is looking for a Principal Biostatistical Programmer to join our Biostatistics team.

You will help biotech, medtech, and specialty pharma companies transform life-changing ideas and breakthrough science into new medicines, devices, and diagnostics. What we do is profoundly connected to saving and improving lives, and we recognize our team members are the most valuable asset in delivering success.

• We are Built for You. We are here to help you grow, to give you the skills and opportunities to excel at work with the flexibility and balance your life requires.
• We are Built by You. Your ideas influence the way we work, and your voice matters here.
• We are Built with You. As an essential part of our team, you help us deliver the medical innovation that patients are desperate for.
  
  

• Develops SAS programs to generate listings, tables and figures as outlined by mock TLF shells
• Performs quality control (source code review, double-programming and log review) of SAS programs
• Develops SAS programs to generate CDISC and other analysis data sets as outlined by respective specifications
• Prepares specifications for CDISC and other analysis data sets
• Assists Data Management with SAS programming needs
• Acts as Lead Biostatistical Programmer to interact with the Lead Biostatistician and the study team
• Develops and validates general SAS macros
  
  

• BS or equivalent from accredited college or university, in statistics, IT, mathematics or closely related field or work related experience to be able to perform this role
• 6-8 years of experience in SAS programming within the area of clinical trials.
• Prior experience using computerized information systems preferred.
• Knowledge of ICH and local regulatory authority drug research and development regulations preferred.
• Advanced knowledge of SAS Software data set architecture, utilities, and programming techniques
• Demonstrated working knowledge of advanced SAS macro development and code generation/management algorithms.