Statistical Programmer
Astek
4 - 14 years
Patna
Posted: 18/12/2025
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Job Description
Key Responsibilities
- Develop, validate, and maintain ADaM datasets , TLFs , and other analytical outputs for clinical trials.
- Support Oncology studies by ensuring accuracy, consistency, and regulatory compliance in all programming deliverables.
- Contribute to ISS/ISE activities , including dataset integration, analysis, and documentation.
- Work closely with statisticians, data managers, and clinical teams to ensure timely and quality delivery.
- Assist in regulatory submissions and RTQs , providing clear, traceable, and compliant programming outputs.
- Collaborate in an agile environment , participating in sprint meetings, planning, and continuous improvement discussions.
- Work with internal tools and platforms, including GSK-specific tools , following established standards and governance.
- Troubleshoot data/programming issues and propose process enhancements.
- Ensure adherence to CDISC standards, good programming practices, and audit-ready documentation.
Required Skills & Qualifications
- 4-14 years of Industrial experience
- Proficiency in R programming
- (Intermediate candidates with strong learning intent and ability to upskill quickly will also be considered.)
- Solid experience in SAS programming , especially in a clinical/biostatistics environment.
- Hands-on expertise in ADaM dataset development and TLF programming .
- Good understanding of CDISC standards and clinical trial data flow.
- Strong problem-solving skills, attention to detail, and ability to work in cross-functional teams.
Preferred Qualifications
- Advanced or Expert-level R Programming skills.
- Experience working on Oncology therapeutic area studies.
- Exposure to ISS/ISE , submission workflows, and regulatory interactions (e.g., RTQs).
- Practical understanding of agile ways of working (Scrum/Kanban).
- Prior experience using or supporting GSK tools and platforms .
Why Join Us?
- Opportunity to work on impactful Oncology research with global teams
- Continuous learning and upskilling environment
- Collaborative, agile work culture
- Exposure to end-to-end statistical programming lifecycle and regulatory submissions
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