General Motors (GM) is looking to evaluate and enhance autonomous vehicle (AV) safety performance by developing and applying sophisticated statistical methods to analyze large-scale data generated by AV systems. This role aims to derive insights that support safety validation, risk assessment, and continuous improvement of autonomous driving technologies to achieve zero accidents.
Requirements
- Proven expertise in applying statistical methods to physics-based systems and advanced sensing technologies
- Strong knowledge of statistical modeling, machine learning, and deep learning techniques
- Experience with causal inference, instrumented variables, and multifactor attribution methods
- Extensive experience analyzing large-scale datasets and generating actionable insights
- Proficiency in SQL and Python programming languages
- Experience with data visualization tools and techniques
Responsibilities
- Develop and standardize statistical estimation practices and uncertainty models for AV safety risk assessments
- Implement scalable performance measurement solutions to ensure safe and compliant AV on-road behavior
- Conduct iterative development processes, sharing early results and identifying emerging safety risks
- Assess bias estimation and subsampling strategies used in system engineering processes
- Support data engineering and software teams in developing automated pipelines and tooling for measurement and risk analysis
- Perform statistical analyses on aggregate and sub-aggregate measures of AV driving software
- Design analyses incorporating driving context and scenario-based factors
Other
- M.S. degree in statistics, operations research, biostatistics, econometrics, or a related quantitative discipline
- Minimum of 8 years of relevant experience, including at least 5 years as a Data Scientist or Statistician in a corporate or government setting
- Excellent communication and interpersonal skills, capable of engaging with both technical and non-technical stakeholders
- Strong business acumen with the ability to evaluate strategic problems and propose data-driven solutions
- Collaborate with cross-functional teams including safety, engineering, data engineering, and legal departments
