Senior Statistical Programming Manager

3 weeks ago


Alameda, California, United States Exelixis Full time
About Us

We are a leading biopharmaceutical company dedicated to creating innovative therapies for cancer patients worldwide. At Exelixis, we are committed to advancing the field of oncology research and developing treatments that make a meaningful difference in people's lives.

We are seeking a highly skilled Senior Statistical Programming Manager to join our team and contribute to our mission of improving patient outcomes through cutting-edge scientific research.

Responsibilities
  • Lead statistical programming activities at the study or project level, using statistical software (mainly SAS) to create and maintain macros, listings, tabulations, graphical summaries, and formal statistical estimates and tests
  • Create datasets in a standard format (i.e., SDTM), analysis datasets, assess quality of data analysis programs, and develop automated analysis tools where appropriate
  • Develop programs to assist with data review such as edit checks and custom listings, and may be responsible for data integration used for clinical summaries and/or creation and quality control of statistical submission components to regulatory agencies
  • Partner with biostatisticians and clinical data management staff in establishing standards for clinical data collection, management and/or reporting of data
Requirements
  • BS/BA degree in related discipline and a minimum of eleven years of related experience; or, MS/MA degree in related discipline and a minimum of nine years of related experience; or, PhD in related discipline and a minimum of five years of related experience; or, Equivalent combination of education and experience
  • May require certification in assigned area
  • At least eight years' experience in Pharmaceutical/Biotech programming
  • Demonstrated proficiency in SAS/Base, SAS/Stat, and SAS/Macros
Compensation

The base pay range for this position is $154,500 - $219,500 annually. The base pay offered will take into account the candidate's geographic region, job-related knowledge, skills, experience and internal equity, among other factors.



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