Associate Director, Medical Analytics and Exploratory Data Science

Revolution Medicines • Redwood City, CA

6h • Hybrid

About The Position

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 highly capable Associate Director of Biostatistics to join our Medical Analytics and Exploratory Data Science Biostatistics group within our Biostatistics organization. This role will play a critical part in the design, analysis, and interpretation of exploratory data analyses, scientific publications, real-world evidence (RWE), post-marketing research, and health economics and outcomes research (HEOR) studies. The successful candidate will serve as a key statistical contributor and emerging leader, partnering closely with cross-functional teams to deliver high-quality, data-driven insights that support scientific understanding and evidence generation.

Requirements

• Ph.D. or M.S. in Statistics/Biostatistics, a minimum of 5 years (for Ph.D.) and 8 years (for M.S.) of experience in biotech/pharma industry as a statistician.
• Solid knowledge of statistical methodologies for oncology, including survival analysis and causal inference.
• Hands-on experience in exploratory analysis of oncology trials.
• Ability to work independently and within a team.
• Ability to independently execute statistical analyses for moderately complex projects with guidance from senior statisticians.
• Familiar with regulatory requirements related to biostatistical activities and clinical trials.
• Strong verbal and written communication skills are required.
• Strong interpersonal and project management skills are essential.
• Proficiency in SAS and/or R.

Nice To Haves

• Knowledge of RWD and health economics and outcomes research (HEOR) in oncology is a plus.
• Familiarity with machine learning or advanced modeling approaches applied to biomedical or observational data.

Responsibilities

• Lead statistical design, analysis, and interpretation for exploratory data analyses using existing clinical trial data, real world data studies, post-marketing research, and HEOR projects.
• Partner closely with other subfunctions within quantitative sciences and with cross-functional teams, including clinical development, medical affairs, safety, statistical programming, regulatory affairs and commercial, to execute evidence generation plans.
• Apply appropriate statistical methodologies, including survival analysis, machine learning, and casual inference approaches, to address complex scientific and medical questions in oncology.
• Contribute to the development of analysis plans, technical specifications, and interpretation of results under general direction from senior statistical leadership.
• Support cross-functional evidence generation planning by providing statistical input into study design, feasibility, and analysis strategies.
• Review and oversee statistical deliverables produced by internal programmers or external vendors/contractors to ensure scientific quality and consistency with standards.
• Contribute to and implement policies, standards, and procedures to ensure consistency and quality in statistical practices.
• Assist with the preparation of scientific communications, including abstracts, manuscripts, posters, and internal presentations.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Education Level: Ph.D. or professional degree