Senior Associate Data Scientist, Pharmacometrics

Position Summary

We are seeking a highly skilled Senior Associate Scientist, Pharmacometrics to work alongside our Pharmacometrics team to optimize, automate, and scale data workflows supporting drug development. This role is ideal for a strong programmer and problem-solver who enjoys transforming complex, manual analytical processes into efficient, reproducible, and well-engineered systems. While prior hands-on experience with PK/PD modeling is not required, the successful candidate will bring a strong technical foundation and a willingness to learn pharmacometrics concepts through close collaboration with domain experts.

Summary Of Key Responsibilities

• Data Workflow Optimization & Tool Development
• Streamline data cleaning, transformation, and QC processes to improve reproducibility, traceability, and robustness of analytical workflows
• Design, develop, and maintain reusable, well-documented code, libraries, and utilities in R and/or Python to support scientific analyses
• Create interactive tools or dashboards to support internal users (e.g., Shiny, Dash)
• Apply software engineering best practices (version control, testing, modular design)
• Support the use and maintenance of the secure working environment
• Communicate user needs with the vendor
• Collaborate with IT and the vendor to support change controls
• Pharmacometrics & PK/PD Enablement (with Training Support)
• Work closely with pharmacometricians to support PK/PD and exposure–response analyses
• Learn foundational PK/PD and modeling concepts on the job
• Translate scientific requirements into robust computational solutions
• Enable faster iteration and insight generation for modeling and simulation activities
• Data & Collaboration
• Partner with Clinical Pharmacology, Statistics, and related quantitative groups
• Support data standards, organization, and metadata practices
• Communicate technical solutions clearly to both technical and non-technical colleagues

Requirements/Qualifications

• MS in Data Science, Computer Science, Statistics, Applied Mathematics, Engineering, or related quantitative field
• Strong programming background in R and/or Python
• Demonstrated experience optimizing, automating, or scaling data analysis workflows
• Experience working with complex scientific or real-world datasets
• Solid understanding of data structures, algorithms, and analytical best practices
• Exposure to regulated environments and audit-ready workflows
• Prior exposure to pharmacometrics, biomedical data, or clinical data would be a plus
• Strong problem-solving skills and curiosity