Senior Systems Data Scientist, Behavior Validation

General Motors•Sunnyvale, CA

1d•$148,000 - $226,200•Hybrid

About The Position

As a Senior Systems Data Scientist on the Behavior Validation team within the Autonomous Vehicle (AV) organization, you will play a pivotal role in establishing pragmatic, data-backed methodologies for measuring trust and confidence in AV behavior validation results across both simulation and real-world road testing. Your expertise in data science and engineering will enable you to design and implement frameworks that correlate simulation and road-based outcomes, simplify complex analytical methods, and support production-ready analysis pipelines that inform AV launch and release decisions. You will collaborate with cross-functional teams—including systems engineers, safety stakeholders, and AI developers—to define confidence metrics, create scalable validation strategies, and ensure that AV behavior meets rigorous safety and performance standards.

Requirements

Advanced degree in Data Science, Computer Science, Engineering, or related fields.
5+ years of experience in data science and analytics, preferably in safety-critical or complex systems domains.
Strong background in simulation-to-road correlation, statistical modeling, and confidence estimation.
Proficiency in Python, SQL, and data visualization tools (e.g., Jupyter, Looker, Tableau).
Ability to simplify complex analytical methods into practical frameworks for production environments.
Excellent communication skills, capable of translating technical insights into clear, actionable recommendations.

Nice To Haves

Experience in autonomous vehicle development, ADAS systems, or robotics.
Familiarity with simulation environments and large-scale data analysis.
Proven ability to design confidence metrics and validation strategies for safety-critical systems.
Experience building dashboards and visualization tools for decision-making.
Strong track record of cross-functional collaboration in high-stakes engineering environments.

Responsibilities

Develop and operationalize data-driven methodologies for measuring trust and confidence in AV behavior validation results.
Establish correlation frameworks between simulation-based and road-based validation outcomes to ensure consistency and reliability.
Simplify complex statistical and analytical methods into production-ready frameworks for AV behavior analysis.
Design and implement scalable analysis pipelines that support continuous release decisions and AV launch readiness.
Collaborate with engineering, safety, and AI teams to define confidence metrics and validation protocols.
Provide actionable insights through data visualization and reporting tools to inform decision-making for AV behavior validation.