Principal Statistical Programmer(ADAM & TLF) in India at Jobgether
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Job Description
This position is posted by Jobgether on behalf of a partner company. We are currently looking for a Principal Statistical Programmer (ADAM & TLF) in India.
This role offers the opportunity to lead high-impact statistical programming activities within clinical development, contributing directly to the generation of reliable evidence that supports regulatory submissions and patient outcomes. You will work in a highly collaborative global environment, partnering with statisticians, clinical teams, and stakeholders to design, validate, and deliver high-quality analysis datasets and statistical outputs. The position combines deep technical expertise in clinical programming with leadership responsibilities, including mentoring junior programmers and shaping best practices. You will play a key role in ensuring data integrity, compliance, and efficiency across complex clinical studies. This is a highly visible role where your work will directly support decision-making in drug development programs. The environment is dynamic, science-driven, and focused on continuous improvement and innovation in clinical analytics.
You will provide technical leadership in statistical programming activities across clinical studies, ensuring high-quality deliverables and compliance with industry standards. You will collaborate closely with cross-functional teams to translate statistical requirements into robust programming solutions that support clinical research and regulatory submissions.
- Lead the development and maintenance of statistical programming standards and best practices across clinical projects
- Design, develop, and validate ADaM datasets and TLF outputs using SAS programming in clinical environments
- Collaborate with statisticians and clinical stakeholders to understand analysis requirements and translate them into programming specifications
- Ensure accuracy, consistency, and integrity of clinical data and statistical outputs across studies
- Perform complex troubleshooting and resolve programming issues in clinical datasets and analysis workflows
- Conduct code reviews and provide mentorship to junior programmers to ensure high-quality deliverables
- Contribute to process improvement initiatives and optimization of programming tools and workflows
- Support study-level leadership, including coordination of programming activities and client interaction where required
The ideal candidate brings strong clinical statistical programming expertise, leadership experience, and deep knowledge of ADaM and TLF development within regulated environments.
- 8+ years of experience in clinical statistical programming using SAS (Base and Advanced SAS)
- Strong expertise in ADaM standards, dataset creation, and TLF programming for clinical trials
- Experience working on integrated datasets, including ISS/ISE and pooled study analyses (preferred)
- Proven ability to lead studies and interact with clients or cross-functional stakeholders
- Solid understanding of safety and efficacy data analysis in clinical research environments
- Strong proficiency in statistical programming languages and data analysis methodologies
- Familiarity with regulatory standards and clinical data requirements
- Strong analytical, problem-solving, and troubleshooting skills
- Excellent communication skills with ability to work in global, cross-functional teams
- Ability to mentor and guide junior programmers and ensure quality standards
- Competitive compensation aligned with experience and industry standards
- Opportunity to work on global clinical trials impacting drug development and patient outcomes
- Career development and progression within a leading life sciences environment
- Collaborative global teams with strong technical and scientific expertise
- Exposure to large-scale, complex clinical datasets and regulatory-grade submissions
- Learning opportunities in advanced statistical programming and clinical analytics
- Inclusive and supportive work culture focused on continuous improvement and innovation