Data Scientist (Autonomous Vehicles)

TL;DR

Data Scientist (Autonomous Vehicles): Designing and implementing quantitative metrics to assess the safety, performance, and passenger comfort of self-driving systems with an accent on statistical validation and large-scale data analysis. Focus on building scalable data pipelines, applying hypothesis testing to complex driving behaviors, and collaborating with engineering teams to ensure system readiness for urban deployment.

Location: Must be based in Austin, TX. Onsite role; no remote options available.

Company

hirify.global is dedicated to advancing autonomous driving technology through data-driven evaluation frameworks that ensure system safety and commercial readiness.

What you will do

• Analyze data from real-world and simulated experiments to evaluate system performance.
• Develop and refine quantitative metrics to assess driving behavior, safety, and passenger comfort.
• Apply statistical inference and hypothesis testing to validate metric reliability.
• Collaborate with autonomy software, simulation, and safety teams to prioritize improvements.
• Build scalable data pipelines to automate metric computation and reporting.
• Review driving logs and participate in test rides to ground analyses in real-world performance.

Requirements

• Authorized to work in the U.S.
• 2+ years of experience in data science, applied statistics, or metrics development.
• Proficiency in Python and SQL for data analysis.
• Strong background in statistical methods including A/B testing and regression.
• Experience designing metrics for complex systems like robotics or autonomous vehicles.
• Proven ability to communicate technical findings to cross-functional stakeholders.

Nice to have

• Experience with machine learning including model evaluation and feature engineering.
• Familiarity with big data tools such as Spark, Hadoop, or MapReduce.
• Knowledge of traffic regulations or automotive safety standards like NHTSA.

Culture & Benefits

• Work on the cutting edge of autonomous vehicle commercialization.
• Collaborative environment with software, simulation, and safety engineering teams.
• Direct impact on safety standards and urban deployment strategies.