Job Description

• Lead the development, validation, and maintenance of statistical programs using SAS to generate tables, listings, and figures (TLFs) for clinical trial data analysis.
• Develop and maintain SDTM domains in accordance with CDISC guidance.
• Create and optimize ADaM datasets, Tables, Figures, Listings (TFLs) and Analysis content.
• Support the creation of statistical outputs for clinical study reports (CSRs), regulatory submissions, and publications.
• Prepare documentation for regulatory submissions, including electronic submissions to the FDA and other global health authorities.
• Perform data cleaning, validation, and preparation tasks to ensure high-quality datasets for analysis.
• Prepare and maintain thorough documentation of programming activities, including specifications, programming code, and validation reports.
• Participate in the development of and ensure compliance to Standard Operating Procedures (SOPs), policies, and guidelines.
• Establish and implement statistical programming standards and comply with industry standards and regulatory requirements among project team members and across all studies.

Requirements:

• Minimum of a bachelor's degree required; MS degree is preferred (statistics, biostatistics, or closely related field).
• 5 years' experience with SAS and clinical programming within the biotech / pharmaceutical industry.
• Proficiency in SAS programming, including experience with SAS macro language, data step programming, and PROC SQL..
• Strong knowledge of CDISC and CDASH standards, including SDTM and ADaM datasets, and experience with regulatory submission requirements.
• Experience with clinical trial data and understanding of the drug development process.
• Proficiency in industry standards, medical terminology, and clinical trial methodologies.
• Excellent problem-solving skills and attention to detail, with the ability to work independently and manage multiple projects simultaneously.
• Strong communication and interpersonal skills, with the ability to collaborate effectively with cross-functional teams.

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