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 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;

• 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.