Jobs / United States / Waymo LLC
Senior Data Science Manager, Driving Quality
Waymo LLC · 🇺🇸 Mountain View, California, USA
Sponsorship verdict
Sponsorship possible
One solid signal, not two — worth applying, and worth asking about sponsorship early.
- Employer is on a government sponsor recordThe US Department of Labor certified 290 H-1B/E-3 labor condition applications for this employer between Oct 2025 and Jun 2026 (latest Jun 2026) — the step every H-1B hire needs first. USCIS also records 87 H-1B approvals in FY2023. Source: LCA disclosure data (US Department of Labor (OFLC)).
- The posting doesn’t mention sponsorshipSilence isn’t a refusal — ask the recruiter before investing much time.
- No salary bar for this routeH-1B has no fixed salary bar: the employer must pay at least the prevailing wage for the role and area. Cap-subject employers enter a lottery weighted by wage level. Source: https://www.federalregister.gov/documents/2025/12/29/2025-23853/weighted-selection-process-for-registrants-and-petitioners-seeking-to-file-cap-subject-h-1b, rules effective 2026-02-27.
- What Waymo LLC paid sponsored hires in similar roles19 certified filings for “Data Scientist” (Data Scientists) in CA: $197k–$230k, median $205k. Most were filed at wage level III (50%) — 3 lottery entries, ≈46% projected selection odds for cap-subject employers. Source: US Department of Labor LCA disclosure data (Oct 2025 – Jun 2026).
- Confirmed live todayWhen a source last listed this job as open.
US H-1B: cap-subject employers enter a lottery weighted by wage level — Level I gets 1 entry, Level IV gets 4 (DHS projected selection odds ≈15% at Level I to ≈61% at Level IV). Universities and non-profit research employers are cap-exempt. The $100,000 fee for new petitions from abroad is currently blocked by a court order (appeal pending).
A verdict summarises public evidence; it is not legal advice and never a guarantee — the employer and the immigration authority decide. Sign in to factor in where you can already work.
Or apply yourself on the official page →
Sponsor Radar — Waymo LLC
The US Department of Labor certified 290 H-1B/E-3 labor condition applications for this employer between Oct 2025 and Jun 2026 (latest Jun 2026) — the step every H-1B hire needs first. USCIS also records 87 H-1B approvals in FY2023. Source: LCA disclosure data (US Department of Labor (OFLC)).
Past sponsorship or register membership never guarantees sponsorship for this vacancy or for you. Full Sponsor Radar for Waymo LLC →
About the role
Waymo is an autonomous driving technology company with the mission to be the world's most trusted driver. Since its start as the Google Self-Driving Car Project in 2009, Waymo has focused on building the Waymo Driver—The World's Most Experienced Driver™—to improve access to mobility while saving thousands of lives now lost to traffic crashes. The Waymo Driver powers Waymo’s fully autonomous ride-hail service and can also be applied to a range of vehicle platforms and product use cases. The Waymo Driver has provided over ten million rider-only trips, enabled by its experience autonomously driving over 100 million miles on public roads and tens of billions in simulation across 15+ U.S. states. Rigorous evaluation of the Waymo Driver is a critical part of scaling our ride hailing service and achieving Waymo’s ambitious goals. In this role, you will lead a data science team specializing in evaluating the Waymo Driver’s ability to comply with rules of the road. Road rule-related behaviors are some of the most challenging to identify, and areas of work include understanding human baseline performance, partnering with ML engineers to improve detection capabilities, and delivering critical insight about the Driver’s current capabilities and opportunities for improvement. In this hybrid role you will report to the DS Lead for Driving Quality. You will: • Define and uphold a high bar for measurement rigor. Ensure we can confidently rely on the evaluation signals informing deployment and scaling decisions. Identify and work to resolve any gaps where current evaluation signals are not scaling with Waymo’s business or providing the necessary actionability for stakeholders. • Develop and adapt our evaluation framework to accommodate road rules across multiple countries. • Collaborate with leads in product, engineering, and systems engineering to align to unlock key Waymo deployment milestones. Be an opinionated partner informing roadmaps for engineering work to improve our measurement capabilities. • Measure performance of the Waymo driver in new territories and hardware platforms, providing input on Waymo’s readiness to scale in new markets. Communicate these findings to senior stakeholders. • Be an active technical contributor on the team, as well as a technical lead and/or manager to several data scientists. Frame and solve ambiguous problems by scoping technical priorities and innovating on statistical methods. Champion data science excellence and provide constructive technical feedback within the team and across Waymo. You have: • Degree in a quantitative field (e.g. Statistics, Mathematics, Physics) • Either a PhD in a quantitative field and 8+ years of industry experience, or 12+ years of industry experience solving data science problems. • Experience as both a technical lead and a people manager. • Experience working in highly cross-functional teams and championing data-driven culture. • Expertise using advanced statistical methods in an applied setting; familiarity with ML systems/models • Demonstrated knowledge of data analysis libraries and packages in Python, R, and/or SQL. We prefer: • PhD in a quantitative field • A demonstrated track record of independently driving data science projects to deliver business value • Experience solving problems related to Autonomous Driving or Ride Hailing. • Experience with large-scale evaluation frameworks for software development. • Experience in adjacent relevant areas like Advanced Machine Learning, Traffic Modeling, Safety Evaluation or Prediction The expected base salary range for this full-time position across US locations is listed below. Actual starting pay will be based on job-related factors, including exact work location, experience, relevant training and education