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Scientist II, Pharmacometrician

Revolution Medicines · Redwood City, California, United States · On-site

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About Revolution Medicines

Backed by GV.

About the role

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.

What they're looking for

  • Ph.D. or equivalent in Statistics, Biostatistics, Mathematics or related field
  • Internship or work experience in biotechnology or pharmaceutical industry to include:
  • 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,
More about this role

Revolution Medicines is a global, commercial-state oncology company dedicated to discovering, developing and delivering innovative medicines for patients with RAS-addicted cancers. Leveraging its differentiated RAS(ON) tri-complex inhibitor platform, the company is advancing a broad, integrated portfolio of oral RAS(ON) inhibitors designed to directly target the active, cancer-driving state of RAS. Founded on rigorous scientific inquiry and a willingness to challenge long-held assumptions, Revolution Medicines is committed to changing the trajectory of disease for patients with RAS-addicted cancers worldwide.

Our people are united by a shared way of working: follow the science, challenge assumptions, act with urgency and hold ourselves to a high standard of rigor—all in service of patients.

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...

Read the full posting on Revolution Medicines's site ↗

Clinical Development

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