Senior Programmer Submission

Accountabilities

• Program and validate clinical datasets and SDTMs, including complex efficacy and laboratory data, ensuring accuracy and compliance with applicable standards.

• Develop complex non-efficacy outputs, tables, figures, and other statistical programming deliverables.

• Perform senior-level reviews and quality control of non-statistical outputs.

• Develop, debug, maintain, and implement complex macros, contributing to the evolution of standard macro libraries.

• Create, review, and update complex dataset specifications for individual and multiple studies, including efficacy datasets and Integrated Summary of Safety (ISS) and Integrated Summary of Efficacy (ISE) deliverables.

• Review complex study designs and Statistical Analysis Plans (SAPs) independently, assess output shells, and provide technical feedback.

• Apply current SDTM and ADaM standards and ensure appropriate implementation throughout the programming lifecycle.

• Support regulatory submission requirements, including FDA Clinical Data Interchange Standards Consortium (CDISC) requirements and the preparation of define.xml and define.pdf documentation.

• Lead programming teams across multiple studies, taking responsibility for the quality, consistency, and timely delivery of outputs and submission packages.

• Coordinate study-level resources and deliverables with study statisticians and project managers, contributing to resource planning and allocation meetings.

• Act as the primary programming contact for assigned teams, proactively resolving technical issues and maintaining effective collaboration.

• Promote programming best practices across clinical trials and ensure adherence to established quality checklists, standard operating procedures (SOPs), and study documentation requirements.

• Maintain and archive study documentation in accordance with applicable procedures.

• Develop and deliver technical training as required, supporting team capability and continuous professional development.

• Create, review, and update programming processes and SOPs, taking responsibility for compliance at the study level.

Requirements

• Bachelor's degree or higher in Computer Science, Mathematics, or a related scientific discipline.

• At least five years of SAS programming experience within the pharmaceutical or contract research organization (CRO) industry; this is essential.

• At least five years of experience working with CDISC standards, including programming SDTM and ADaM datasets.

• Strong practical experience with Pinnacle 21 (P21) for clinical data validation.

• Experience with Integrated Summary of Safety (ISS), regulatory submissions, and/or Bioresearch Monitoring (BIMO) activities.

• Solid understanding of clinical trial design, implementation, and common clinical research challenges.

• Familiarity with Good Clinical Practice (GCP) and relevant regulatory requirements.

• Demonstrated ability to lead programming activities across multiple studies while balancing technical delivery, quality assurance, and resource management.

• Strong analytical, problem-solving, and debugging skills, with the ability to review complex programming outputs and specifications independently.

• Effective communication and collaboration skills, including the ability to work with statisticians, project managers, technical teams, and other stakeholders.

• A proactive approach to technical leadership, continuous improvement, documentation, and adherence to quality standards.

• Experience with R programming is preferred.

• Previous regulatory submission experience is preferred.

Benefits

• Competitive compensation: A competitive salary and benefits package; the specific salary range is not disclosed in the available posting.

• Flexible working arrangements: Remote work is available, with the original posting indicating that candidates can be based anywhere in India.

• Flexible hours: Part-time working hours may be available.

• Training and development: Structured training plans and ongoing opportunities to develop technical and professional skills.

• Continuous learning: Opportunities to build expertise in clinical programming, regulatory submissions, and evolving data science practices.

• Supportive working environment: A collaborative, friendly culture focused on quality, technical excellence, and teamwork.

• Work-life balance: An emphasis on supporting employees in maintaining a healthy balance between work and personal commitments.