Associate Director, Technology & Scientific Computing

Summary

We are seeking a highly experienced Lead Business Analyst with strong pharmaceutical domain expertise and deep R programming capabilities to support a global pharmaceutical engagement.

This role will act as the primary interface between business stakeholders, biostatisticians, statistical programmers, and technical delivery teams. The candidate will be responsible for translating clinical, statistical, and operational requirements into scalable R-based analytics platforms, automation workflows, and enterprise reporting solutions.

The ideal candidate should demonstrate strong domain understanding of clinical trials, regulatory expectations, and statistical workflows, along with the ability to independently manage initiatives and coordinate cross-functional teams.

• Act as the primary interface between business stakeholders, biostatisticians, statistical programmers, and technical teams.
• Lead requirement gathering workshops and translate clinical/statistical needs into structured functional and technical specifications.
• Ensure alignment between Statistical Analysis Plans, reporting outputs (TLFs), and system implementation.
• Drive end-to-end requirement traceability across development, validation, and deployment phases.
• Oversee design and delivery of scalable R-based analytics applications and Shiny dashboards.
• Ensure regulatory compliance, audit readiness, and adherence to documentation and governance standards.
• Provide structured updates on progress, risks, dependencies, and mitigation plans.

• 14+ years of experience in analytics, statistical programming, or software development. Proven experience in pharmaceutical or clinical research domain engagements.
• Advanced R programming (data manipulation, statistical modelling, visualization).
• Strong experience with Shiny for interactive dashboards and web applications.
• Experience with Posit platform tools (Workbench, Connect, Package Manager) or equivalent.
• Expertise in statistical computing and analytics solution design.
• R package development and familiarity with CRAN/Bioconductor libraries.
• Proficiency in SQL and relational databases. Strong understanding of Git version control (branching strategy, pull requests, release coordination).
• Experience integrating R with enterprise systems, APIs.
• Strong understanding of clinical trial lifecycle.

Helping people with disease and their families takes more than innovative science. It takes a community of smart, passionate people like you. Collaborating, supporting and inspiring each other. Combining to achieve breakthroughs that change patients’ lives. Ready to create a brighter future together?

Learn about all the ways we’ll help you thrive personally and professionally.

Read our handbook (PDF 30 MB)