Director of Pharmacometrics

Revolution Medicines is a clinical-stage precision oncology company focused on developing novel targeted therapies to inhibit frontier targets in RAS-addicted cancers.  The company’s R&D pipeline comprises RAS(ON) Inhibitors designed to suppress diverse oncogenic variants of RAS proteins, and RAS Companion Inhibitors for use in combination treatment strategies. As a new member of the Revolution Medicines team, you will join other outstanding Revolutionaries in a tireless commitment to patients with cancers harboring mutations in the RAS signaling pathway.

The Opportunity:

We are seeking a passionate and experienced individual with strong statistical modeling background to be part of the Nonclinical Development and Clinical Pharmacology (NDCP) Organization. 

As a key member of the pharmacometrics group, you will:

• Develop and apply advanced statistical and machine learning methodologies to address complex scientific questions in PK/PD and exposure-response analysis.

• Design and implement model-based meta-analysis (MBMA) frameworks to integrate internal PKPD data and external data to inform clinical pharmacology strategies.

• Provide statistical and quantitative modeling support for key development decisions, including dose optimization and RP2D selection.

• Collaborate cross-functionally to ensure modeling approaches are scientifically rigorous, fit-for-purpose, and aligned with program objectives.

• Contribute to the continuous advancement of quantitative science capabilities, including method development, best practices, and adoption of innovative analytical approaches.

Required Skills, Experience and Education:

• PhD in Statistics/Biostatistics, Pharmaceutical Sciences or MS in Statistics with five years of experience in MBMA in pharmaceutical industry.

• Solid knowledge and hands-on experience in hierarchical models and Bayesian inference are required.

• Solid knowledge and hands-on experience in standard statistical modeling (generalized linear models, survival models, mixed models, etc) are required.

• Demonstrated experience in meta-analysis, including the application of appropriate statistical methods to model between-study variabilities.

• Proficiency in statistical programming using R.

• Excellent verbal and written communication skills, and ability to clearly convey complex concepts and findings to both non-specialist and specialist audiences.

• Experience and track record in clinical-stage drug development.

Preferred Skills: 

• Prior experience with small molecules in oncology drug development.

• Local candidates are preferred, but strong remote candidates will be considered.

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