Job Description

About the Team

Our team develops the metrics and evaluation frameworks that measure the safety, performance, and real-world readiness of autonomous driving systems. We work closely with engineering, simulation, and safety teams to analyze large volumes of real-world and simulated driving data, enabling data-driven decisions that accelerate deployment.

Our work answers critical questions such as:

• How does the system perform in complex urban scenarios?
• Does vehicle behavior meet passenger comfort and safety expectations?
• How do we statistically validate readiness for deployment at scale?

About the Role

We are looking for a Data Scientist to help define, build, and validate metrics that evaluate autonomous driving behavior. In this role, you will design quantitative measures of safety, performance, and passenger experience, apply statistical techniques to large datasets, and partner closely with cross-functional teams to guide system improvements.

This position offers a chance to work on high-impact problems at the intersection of data science, safety, and autonomous systems.

What You’ll Do

• Analyze large-scale datasets from real-world and simulated autonomous driving experiments
• Design, implement, and iterate on quantitative metrics (rule-based and ML-driven) for driving behavior, safety, and passenger comfort
• Apply statistical inference and hypothesis testing to assess metric reliability, sensitivity, and significance
• Collaborate with autonomy software, simulation, and safety teams to prioritize improvements based on data insights
• Build and maintain scalable pipelines to automate metric computation and reporting
• Review driving logs and participate in test rides to ground analysis in real-world system behavior

What You’ll Need

• 2+ years of experience in data science, applied statistics, or metrics development
• Strong proficiency in Python and SQL for data analysis
• Solid foundation in statistical methods (e.g., hypothesis testing, confidence intervals, regression, A/B testing)
• Experience designing metrics for complex systems (e.g., robotics, autonomous systems, or large-scale software platforms)
• Ability to clearly communicate technical findings to cross-functional partners

Nice to Have

• Experience with machine learning , including model evaluation or feature engineering
• Familiarity with big data tools (e.g., Spark, Hadoop, MapReduce)
• Knowledge of traffic regulations or automotive safety standards

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