Our vehicles are on the road in California, Arizona, and Michigan navigating some of the most challenging and unpredictable driving environments. We’re hiring people who want to solve some of today’s most complex engineering challenges and make a positive impact.
In this role you will determine, with statistical confidence, when our vehicles are safer than human drivers.
Statistical estimation and uncertainty modeling
Bias estimation and subsampling strategies
Account for intrinsic nonstationarity in underlying process performance
Significance testing of system requirements
Rendering precise formulations of ambiguous problem statements
3+ years of practical experience in statistical estimation
Facility with standard statistical methods like linear and logistic regression, SVM, instrumental variables, confidence intervals, significance testing.
Extra points for prior Practical command of Python and/or R or similar analytical tools
Excellent communication skills
Extensive practical experience in statistical data analysis
PhD in a quantitative discipline (statistics, operations, biostatistics, econometrics, etc.)
Prior experience with rare event statistics
Bonus points for academic/industry experience in applying Bayesian methods, MCMC, Gibbs Sampling to real world problems.
Extra points for experience with active learning methods (Multiarm-Bandit, Active Thompson Sampling etc)
Prior experience in a related robotics or autonomy discipline