Statistical Programmer

Industry: Pharmaceuticals / Biotechnology / Clinical Research Education: Bachelor's or Master's Degree in Computer Science, Statistics, Mathematics, Data Science, Life Sciences, or a related discipline Role Overview We are seeking an experienced SAS Programmer to support clinical data programming for clinical studies and regulatory submissions. The role involves developing, validating, and maintaining SAS programs for data transformation, statistical analysis, and reporting while ensuring compliance with CDISC standards, GxP requirements, and applicable regulatory guidelines. The successful candidate will collaborate with Data Management, Biostatistics, and Clinical Operations teams to deliver accurate, high-quality, and timely programming deliverables. Key Responsibilities Develop, validate, and maintain SAS programs for SDTM, ADaM, and TLF datasets. Translate study protocols, SAPs, and business requirements into efficient SAS programs. Perform data extraction, transformation, integration, and validation from multiple clinical data sources. Generate Tables, Listings, and Figures (TLFs) for clinical study reports and regulatory submissions. Develop edit checks and validation programs for data cleaning and quality assurance. Perform ad hoc statistical analyses and reporting. Collaborate with cross-functional teams to resolve data issues and ensure data integrity. Ensure compliance with GxP, ALCOA, CDISC, SOPs, and regulatory requirements. Manage multiple projects while meeting timelines and quality expectations. Participate in project meetings and proactively communicate risks. Required Qualifications 410 years of SAS Programming experience in pharmaceutical, biotechnology, or clinical research. Strong expertise in SDTM, ADaM, and TLF development. Experience supporting clinical trial programming and regulatory submissions. SAS Certification preferred. Good understanding of CDISC standards, clinical trial processes, GxP, ALCOA, and SDLC. Strong analytical, problem-solving, and communication skills. Ability to manage multiple priorities and collaborate effectively. Experience with SAS statistical analysis and visualization is an advantage. Preferred Qualifications Experience supporting global clinical studies and regulatory submissions. Knowledge of pharmaceutical R&D processes. Ability to work independently in cross-functional environments. .