Statistical Programmer

Job Title: Statistical Programmer Clinical Data (SAS/R)

Location: Pan India

Experience: 3 12 years

Industry: Pharmaceuticals / Biotechnology / Clinical Research

About the Role

We are looking for an experienced Statistical Programmer to oversee programming activities for clinical trials, regulatory submissions, and integrated analyses. This role involves leading a team, ensuring high-quality deliverables, and developing efficient programming standards to support drug development.

Key Responsibilities

• Lead statistical programming activities for a compound or therapeutic area.
• Manage, mentor, and guide a team of statistical programmers.
• Create and validate analysis data sets (ADaM), tables, listings, and figures (TFLs) following CDISC standards.
• Develop and validate Integrated Summary of Safety (ISS) and Integrated Summary of Efficacy (ISE) reports.
• Ensure accuracy and consistency across clinical studies and integrated data.
• Develop, test, and implement reusable standard programs and SAS macros to automate routine tasks.
• Prepare reviewer guides, data definition documents, and other materials for regulatory filings.
• Collaborate with cross-functional teams including Statisticians, Clinical Data Management, Medical Writing, Regulatory, and Clinical Operations.
• Accurately estimate programming efforts and ensure timely project delivery.

Required Skills

• Strong proficiency in SAS programming; experience with R preferred.
• In-depth knowledge of CDISC standards (ADaM, SDTM).
• Experience with regulatory submissions (FDA, EMA) and clinical study lifecycle.
• Knowledge of therapeutic areas such as Oncology, Immunology, Neuroscience.
• Strong communication and leadership skills to guide teams and manage stakeholders.
• Ability to handle multiple priorities and deliver high-quality results under deadlines.

Why Join Us?

• Work on cutting-edge clinical trials and regulatory submissions.
• Collaborate with a team of top-tier professionals.
• Opportunity to develop advanced programming frameworks and drive innovation in data analytics.