SAS Programmer: Clinical Trials & SDTM/ADaM

CHANDRAWAR IT TECHNOLOGIES PVT LTD; Sale; On-site; GBP 35,000 - 60,000; Full time

Job summary

CHANDRAWAR IT TECHNOLOGIES PVT LTD is seeking a skilled SAS programmer to support clinical trial data programming and reporting in a regulated environment. The role focuses on developing, validating, and maintaining SAS programs, creating TLFs, and contributing to CDISC-compliant SDTM/ADaM datasets; collaboration with biostatisticians and data managers is essential.

The position requires attention to data quality, reproducibility and documentation, with opportunities to contribute to study

Responsibilities

• Develop, maintain and validate SAS programs for clinical trial data.
• Create and validate analysis datasets, tables, listings and figures (TLFs).
• Support the development of SDTM and ADaM datasets in accordance with CDISC standards.
• Perform statistical programming for safety and efficacy analyses.
• Review programming specifications and statistical analysis plans.
• Perform quality control checks and investigate discrepancies.
• Develop and maintain SAS macros and reusable programming utilities.
• Ensure programming outputs are accurate, reproducible and properly documented.
• Support data review and reconciliation activities.
• Collaborate with biostatisticians, data managers and clinical project teams.
• Contribute to clinical study reports and regulatory submission deliverables where required.
• Follow company standard operating procedures, programming standards and quality processes.

Skills

SAS programming

SAS macros

CDISC standards

Quality control

Tools

SAS

SAS Macros

CDISC SDTM/ADaM

Job description

CHANDRAWAR IT TECHNOLOGIES PVT LTD is seeking a skilled SAS programmer to support clinical trial data programming and reporting in a regulated environment. The role focuses on developing, validating, and maintaining SAS programs, creating TLFs, and contributing to CDISC-compliant SDTM/ADaM datasets; collaboration with biostatisticians and data managers is essential.

The position requires attention to data quality, reproducibility and documentation, with opportunities to contribute to study