Associate Director SAS Programming

• Provide statistical programming leadership across clinical development programs from study start-up through database lock, submission, and post-submission activities.
• Lead the planning, development, review, and delivery of SAS programming outputs, including SDTM, ADaM, tables, listings, figures, submission datasets, and associated documentation.
• Ensure programming deliverables meet CDISC standards, regulatory expectations, internal SOPs, and quality requirements.
• Partner with Biostatistics, Clinical Data Management, Clinical Operations, Medical Writing, Regulatory Affairs, and Quality to define programming needs, timelines, and deliverables.
• Develop, maintain, and enhance reusable SAS macros, programming standards, templates, utilities, and validation processes.
• Use GitHub or GitLab to manage source control, branching, code review, pull/merge requests, documentation, and traceable programming workflows.
• Develop or support R-based programming solutions, including R Shiny applications, for clinical data visualization, reporting, operational insights, and stakeholder decision-making.
• Review programming specifications, code, outputs, and technical documentation for accuracy, consistency, completeness, and inspection readiness.
• Provide technical oversight, guidance, and mentorship to internal programmers, CROs, offshore teams, and other external programming resources as applicable.
• Support regulatory submission preparation and respond to agency questions, data requests, and post-submission programming needs.
• Identify and implement opportunities to improve programming efficiency, automation, reproducibility, quality, and cross-functional visibility.
• For Director-level consultants, advise on programming strategy, resourcing, vendor oversight, operating-model design, and departmental priorities.

The ideal candidate brings deep SAS clinical programming experience, strong knowledge of CDISC and regulatory submission requirements, and practical experience using GitHub or GitLab for version control. Experience with R programming and R Shiny is required. Python experience is a plus but not required., * Bachelor’s degree in Statistics, Biostatistics, Computer Science, Mathematics, Life Sciences, or a related discipline; advanced degree preferred.

• Associate Director-level candidates should bring approximately 8+ years of clinical statistical programming experience.
• Director-level candidates should bring approximately 10+ years of clinical statistical programming experience, including leadership of programming teams, vendors, or complex clinical development programs.
• Extensive hands-on SAS programming experience in biotech, pharmaceutical, CRO, or another regulated clinical research environment.
• Strong experience producing SDTM, ADaM, tables, listings, figures, and regulatory submission deliverables.
• Thorough knowledge of CDISC standards, including SDTM and ADaM, plus familiarity with FDA, EMA, and/or other global regulatory submission expectations.
• Proven experience using GitHub or GitLab, including version control, branching, pull/merge requests, code review, documentation, and controlled release workflows.
• Required hands-on experience with R programming and R Shiny application development or support.
• Demonstrated experience creating reproducible, validated, and well-documented programming workflows.
• Strong ability to work independently in a remote consulting environment, manage competing priorities, and communicate effectively with senior cross-functional stakeholders.
• Experience leading internal programming teams, CROs, offshore resources, and/or external vendors is strongly preferred.

Preferred Qualifications

• Python experience for automation, analytics, data processing, or visualization is preferred but not required.
• Experience supporting NDA, BLA, MAA, or other global regulatory submissions.
• Familiarity with validated R environments, R package governance, cloud-based analytics platforms, or modern software-development practices.
• Experience working in lean, fast-paced, or high-growth biotech environments. xrbllit
• Experience supporting clinical development programs across multiple therapeutic areas.