Sr. SAS Programmer Job at Katalyst Healthcares and Life Sciences, Richmond, VA

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  • Katalyst Healthcares and Life Sciences
  • Richmond, VA

Job Description

Job Description:
We are seeking a highly skilled Senior Statistical Programmer to join our growing Biometrics team. The ideal candidate will be responsible for providing advanced programming support for the analysis and reporting of clinical trial data in compliance with regulatory requirements. This role will involve working closely with Biostatisticians, Data Managers, and Clinical Teams to deliver high-quality datasets, tables, listings, and figures (TLFs).

Responsibilities:
  • Develop, validate, and maintain SAS programs to generate analysis datasets (ADaM, SDTM) and TLFs for clinical trial submissions.
  • Ensure programming deliverables are accurate, efficient, and compliant with CDISC standards and regulatory guidelines.
  • Collaborate with Biostatistics and Data Management teams to understand study requirements and timelines.
  • Participate in the development of programming standards, macros, and process improvements.
  • Provide mentorship and guidance to junior programmers and review their work for quality and accuracy.
  • Support regulatory submissions (FDA, EMA, PMDA) by preparing submission-ready datasets and documentation.
  • Troubleshoot and resolve complex programming issues independently.
Requirements:
  • Bachelor's or master's degree in Statistics, Computer Science, Mathematics, Life Sciences, or related field.
  • 5+ years of experience as a Statistical Programmer in the pharmaceutical, biotechnology, or CRO industry.
  • Strong proficiency in SAS programming; knowledge of R or other statistical software is a plus.
  • In-depth knowledge of CDISC SDTM and Adam standards.
  • Experience supporting Phase I-IV clinical trials and regulatory submissions.
  • Excellent problem-solving, communication, and organizational skills.
  • bility to work both independently and in a team-oriented environment.
  • Experience with eCTD submissions and regulatory agency interactions.
  • Familiarity with oncology, rare disease, or other therapeutic areas.
  • Knowledge of data visualization tools (e.g., R Shiny, Spotfire).

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