Sr. Statistical Programmer

Responsibilities:

• Develop and maintain SAS programs to create complete SDTM and ADaM datasets and TFLs, and perform QC of SDTM, ADaM, and TFLs
• Produce Define XML/PDFs, Analysis Results Metadata (ARM), aCRFs and Reviewers Guides to support SDTM and ADaM
• Develop and/or lead the development of complex specifications for SDTM and ADaM datasets and contribute to the development of therapeutic area standards
• Review SAPs and TFL shells from a programming perspective for studies and advise on the development of complex TFL shells from a programming perspective
• Mentor less-experienced programmers in the processes around SDTM, ADaM, and TFLs ensuring adherence to department practices and processes
• Present and share knowledge at department meetings
• Respond to QA and client audits and support qualification audits
• Contribute to proposal activities and participate in bid defenses meetings in order to win new business
• Continually identify and suggest ways to improve the efficiency, quality, and productivity of statistical programming

Requirements:

• Bachelor's degree in Mathematics, Statistics, Life Science, Health Science or other relevant scientific field, or equivalent work experience is required.
• 5+ years relevant experience within the Pharmaceutical, CRO or Biotech industry, or equivalent is required.
• Advanced knowledge of Base SAS, SAS Graph, and SAS macro language required.
• SAS certification preferred, emphasis given to Clinical Trials Programming and/or Advanced Programming Using 9.4.
• Experience working in a multi-functional environment and ability to adapt to different ways of working and development methodologies is required.
• Proven track record of effective communication skills, including strong verbal and written communication, influencing, and partnering skills is required.
• Experience as lead statistical programmer on complex studies in clinical research Knowledge in all aspects of clinical trials from initial study set-up to study completion with an excellent understanding of the roles and responsibilities of all related disciplines, e.g., Biostatistics and Clinical Data Management.
• Broad knowledge of all CDISC requirements related to SDTM and ADaM, including define.xml, Reviewer's Guide and submission standards
• Basic competency in R a plus, but not required