Statistical Programmer

5 hours ago

india, IN Astek Full time

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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