Summary

Revolution Medicines is a clinical-stage precision oncology company focused on developing novel targeted therapies for RAS-addicted cancers. The company is pioneering a new class of therapeutics that target oncogenic RAS mutations, which are among the most common drivers of human cancers. Revolution Medicines employs a unique approach to drug discovery, leveraging deep insights into RAS biology to develop small molecule inhibitors that can address previously undruggable targets. Their pipeline includes multiple clinical-stage candidates designed to inhibit various RAS pathway mutations, with a particular focus on KRAS G12C and other RAS variants. The company's scientific platform combines structural biology, medicinal chemistry, and computational approaches to design highly selective inhibitors. Revolution Medicines aims to transform cancer treatment by developing therapies that can overcome resistance mechanisms and provide durable clinical benefits for patients with RAS-driven malignancies. Their research represents a significant advancement in the field of targeted cancer therapy, addressing one of the most challenging areas in oncology drug development.

Job description

The Opportunity

Be a statistical modeler and support the pharmacometrics functions in the department.
Build standard statistical models to conduct standard exposure-response (ER) analysis and drug-drug interaction (DDI) analysis in clinical studies.
Develop and apply state-of-the-art statistical and machine learning methods to identify the associations between exposures and responses.
Interpret ER results to guide dose-finding decisions.

Required Experience, Skills, and Education

Ph.D. or equivalent in Statistics, Biostatistics, Mathematics or related field.
Internship or work experience in biotechnology or pharmaceutical industry.
Track record of applying statistical methods to real-world datasets, including implementing advanced statistical methods.
Presenting complex concepts and results to both specialist and non-specialist audiences in biotech or pharmaceutical setting.
Knowledge and hands-on experience in hierarchical models and Bayesian inference, with application to real-world data.
Demonstrated experience in statistical modeling, including generalized linear models (GLMs), survival models, and mixed-effects models.
Proficiency in R and/or SAS programming.
This position allows for a hybrid work arrangement. The employee must reside in the San Francisco Bay area and may work remotely two (2) days per week.
Successful completion of background and employment history verification required.

Requirements

Ph.D. or equivalent in Statistics, Biostatistics, Mathematics or related field
Internship or work experience in biotechnology or pharmaceutical industry
Track record of applying statistical methods to real-world datasets, including implementing advanced statistical methods
Presenting complex concepts and results to both specialist and non-specialist audiences in biotech or pharmaceutical setting
Knowledge and hands-on experience in hierarchical models and Bayesian inference, with application to real-world data
Demonstrated experience in statistical modeling, including generalized linear models (GLMs), survival models, and mixed-effects models
Proficiency in R and/or SAS programming
Must reside in the San Francisco Bay area
Successful completion of background and employment history verification required

Benefits

Competitive cash compensation
Equity awards
Health benefits
Learning and development opportunities

Company overview

Revolution Medicines is a clinical-stage precision oncology company focused on developing novel targeted therapies for RAS-addicted cancers. The company is pioneering a new class of therapeutics that target oncogenic RAS mutations, which are among the most common drivers of human cancers. Revolution Medicines employs a unique approach to drug discovery, leveraging deep insights into RAS biology to develop small molecule inhibitors that can address previously undruggable targets. Their pipeline includes multiple clinical-stage candidates designed to inhibit various RAS pathway mutations, with a particular focus on KRAS G12C and other RAS variants. The company's scientific platform combines structural biology, medicinal chemistry, and computational approaches to design highly selective inhibitors. Revolution Medicines aims to transform cancer treatment by developing therapies that can overcome resistance mechanisms and provide durable clinical benefits for patients with RAS-driven malignancies. Their research represents a significant advancement in the field of targeted cancer therapy, addressing one of the most challenging areas in oncology drug development.