Lead Data Scientist – Autonomous Driving

Austin, Texas Autonomous Delivery Full-time Posted Aug 19, 2026
Apply on Avride (opens in a new tab) Sourced via job-boards.greenhouse.io · Posted 2026-08-19

About this role

Avride is hiring a Lead Data Scientist – Autonomous Driving, full-time, on-site in Austin, Texas, in the Autonomous Delivery sector.

About the team

Our team is responsible for understanding how our technology performs and turning that understanding into confident decisions. We bring together simulation data, real-world driving data, structured test results, and human-labeled data to evaluate the stack end to end. We collaborate across the stack and deliver analytics on a wide range of technology aspects, from low-level hardware and performance to behavior quality in specific road scenarios. We answer questions from issues with system performance in specific conditions to how ready we are overall to launch from a safety perspective.

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.

Description from Avride's official posting. Always confirm details on the company careers page.

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About Avride

Avride

Company in the mobility sector tracked nightly on the Mobility Jobs board.

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Larry Sherwood Jr.

About Larry Sherwood Jr.

Talent Acquisition Leader specializing in mobility, EV, and frontier tech. 1,200+ hires across roles ranging from production technicians to VPs, including 48 hires for the AFEELA U.S. launch at Sony Honda Mobility (98% offer acceptance, about $1.5M in agency fees avoided). SHRM-CP certified. Build recruiting functions from scratch, no agencies.

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Curated by Larry Sherwood Jr. on the free Mobility Jobs board. Pulled nightly from company applicant tracking systems. Apply directly on the source link above to be considered.