Lead Data Scientist - Autonomous Driving

About the role

We are building the analytics function and looking for people with a leadership mindset and deep analytics experience. You will lead a focus area in evaluation and experimentation, help hire and shape the IC team, guide analysts on scope and methods, and work closely with partner teams. You will integrate simulation and on-road evidence, use a broad toolkit of analytical methods, and produce clear, action-oriented outputs for stakeholders. You are comfortable staying hands-on as an individual contributor.

What you'll do

• Understand the technology deeply. Go deep into autonomous driving technology across behavior and hardware. Evaluate platform health and system behavior, and define the right metrics and metric hierarchy to quantify technology quality.
• Help build and lead the team. Contribute to team formation, take part in hiring and leveling up analysts, and set direction for an evaluation focus area while collaborating with technology leaders and with teams that build data infrastructure and analytics tools.
• Be hands-on with experiments. Design, run, and interpret experiments using solid statistical methods. Be ready to analyze results yourself and translate them into well-supported decisions.
• Build and automate analysis. Collaborate with data engineers and backend developers to assemble datasets and productionize analysis pipelines that automate recurring computations with attention to performance and reliability.

What you'll need

• Experience: 4+ years in analytics for a large-scale or complex technology product.
• Statistics: strong background in statistical reasoning and methods for evaluating change and uncertainty.
• Coding: strong Python and SQL; you can independently run experiments and ship analyses and pipelines end to end.
• Leadership: proven technical leadership, mentoring, and hiring experience in analytics.

Nice to have

• Formal training in statistics (for example, MS or PhD in Statistics, Applied Statistics, Biostatistics, Econometrics, or a quantitative field with rigorous statistical coursework).
• Familiarity with the modern data stack and experience in data engineering.
• Background in autonomy or other technologically intensive domains.

• #LS-MS1
• Candidates are required to be authorized to work in the U.S. The employer is not offering relocation, sponsorship, and remote work options are not available.