Associate Director, Technology & Scientific Computing

Position Overview

This role serves as the main liaison connecting business stakeholders, biostatisticians, statistical programmers, and technical teams, ensuring streamlined communication and collaboration. The candidate will lead workshops to elicit requirements and translate clinical and statistical needs into well-defined functional and technical specifications. They will also oversee the consistency between Statistical Analysis Plans, tabulation, listings, and figures (TLFs), and the implemented system.

Key Responsibilities

• Serve as the primary contact bridging stakeholders and technical teams.
• Conduct requirement gathering sessions and convert clinical/statistical needs into detailed technical documentation.
• Maintain alignment and traceability from requirements through development, validation, and deployment.
• Manage the design and delivery of scalable R-based analytics applications and interactive Shiny dashboards.
• Ensure compliance with regulatory standards and audit readiness by maintaining proper documentation and governance practices.
• Communicate progress, risks, dependencies, and mitigation strategies in a structured manner.

Minimum Qualifications

• Over 14 years of experience in analytics, statistical programming, or software engineering, especially in pharmaceutical or clinical research environments.
• Advanced expertise in R programming including data manipulation, statistical modeling, and visualizations.
• Demonstrated experience developing Shiny interactive dashboards and web applications.
• Familiarity with Posit platform tools such as Workbench, Connect, and Package Manager or equivalent technologies.
• Proven skills in designing statistical computing and analytics solutions.
• Experience creating R packages and working with CRAN/Bioconductor libraries.
• Strong knowledge of SQL and relational database management.
• Proficient understanding and practical use of Git version control including branching strategies, pull requests, and release coordination.
• Experience integrating R with enterprise systems and APIs.
• Thorough understanding of the clinical trial lifecycle.