Statistical Programmer

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