Senior 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 5-14 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