Associate Director, Medical Analytics and Exploratory Data Science

Revolution Medicines • Redwood City, CA

7d • Hybrid

About The Position

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.
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.

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: Director
• Education Level: Ph.D. or professional degree