Senior Statistical Programmer / Statistical Programming Lead

Bwise Solutions; Bengaluru; On-site; INR 4,500,000 - 7,500,000; Full time

Job summary

Bwise Solutions in Bengaluru, Karnataka, is seeking an experienced Clinical Statistical Programmer with a focus on Oncology to join our biostatistics team. You will develop and validate TLFs (Tables, Listings, Figures) using SAS and R, create SDTM/ADaM datasets, and support CSR deliverables and regulatory submissions.

The role requires 7+ years in clinical statistical programming, strong expertise in survival analyses (PFS/OS/ORR/DOR), and collaboration across cross-functional teams.

Qualifications

• 7+ years of relevant experience in clinical statistical programming.
• Hands-on expertise in SAS and R.
• Experience in Oncology clinical trials.
• Strong knowledge of CDISC SDTM and ADaM.
• Hands-on experience in TLF programming.
• Experience with efficacy and safety programming.
• Knowledge of survival/time-to-event analyses.
• Experience with Oncology endpoints such as PFS, OS, ORR and DOR.
• Experience in validation/QC and regulatory submission programming is desirable.
• Strong analytical, problem-solving, communication, and stakeholder-management skills.

Responsibilities

• Perform statistical programming activities for clinical trials across various phases, focusing on Oncology studies.
• Develop, program, review, and validate Tables, Listings, and Figures (TLFs) using SAS and R.
• Create and maintain SDTM and ADaM datasets per CDISC standards.
• Perform programming for efficacy and safety analyses.
• Work on Oncology-specific endpoints and analyses (PFS, OS, ORR, DOR) and time-to-event analyses.
• Demonstrate hands-on SAS and R programming on live clinical studies.
• Develop production-quality programs, perform checks, validation, and QC.
• Support statisticians in development/review of analysis datasets and TLFs.
• Collaborate with Biostatistics, Clinical Data Management, Data Standards, Medical Writing, and cross-functional teams.
• Support preparation of statistical programming deliverables for CSR and regulatory submissions.

Skills

SAS

R

Oncology

CDISC SDTM/ADaM

TLF programming

Regulatory submission

Survival analysis

Stakeholder management

Job description

Role & responsibilities

• Perform statistical programming activities for clinical trials across various phases, with a strong focus on Oncology studies.
• Develop, program, review, and validate Tables, Listings, and Figures (TLFs) using SAS and R.
• Create and maintain SDTM and ADaM datasets in accordance with CDISC standards.
• Perform programming for efficacy and safety analyses.
• Work on Oncology-specific endpoints and analyses including:
• Progression-Free Survival (PFS)
• Overall Survival (OS)
• Objective Response Rate (ORR)
• Duration of Response (DOR)
• Time-to-event / survival analyses
• Kaplan-Meier analyses
• Demonstrate hands-on programming experience in both SAS and R on live clinical studies.
• Develop production-quality programs and perform programming checks, validation, and QC.
• Support statistical programmers and biostatisticians in the development and review of analysis datasets and TLFs.
• Work closely with Biostatistics, Clinical Data Management, Data Standards, Medical Writing, and other cross-functional teams.
• Support preparation of statistical programming deliverables for Clinical Study Reports (CSR).
• Contribute to regulatory submission-related programming and documentation for agencies such as FDA/EMA, where applicable.
• Review specifications, programming requirements, analysis plans, and study documentation.
• Troubleshoot programming issues and ensure timely delivery of high-quality study outputs.

Preferred candidate profile

• 7+ years of relevant experience in Clinical Statistical Programming.
• Strong hands-on expertise in SAS and R.
• Strong experience in Oncology clinical trials.
• Strong knowledge of CDISC standards SDTM and ADaM.
• Hands-on experience in TLF programming.
• Good understanding of clinical trial data and statistical analysis concepts.
• Experience with efficacy and safety programming.
• Knowledge of survival analysis / time-to-event analysis.
• Experience with Oncology endpoints such as PFS, OS, ORR and DOR will be highly preferred.
• Experience in validation/QC and regulatory submission programming is desirable.
• Strong analytical, problem-solving, communication, and stakeholder-management skills.