Staff Product Data Scientist, Experimentation
Waymo
$230,000 - $284,000 / year
Applying takes a free account: you'll come right back to this job to finish with your profile.
Need a reasonable accommodation to apply or interview? Contact us.
JobMinglr uses automated technology to recommend jobs based on profile information and job preferences. Match Score does not determine eligibility for a position, prevent a user from viewing or applying to a job, or make hiring decisions on behalf of an employer.
Description
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.
Waymo’s Product Data Science team works cross-functionally with Engineering, Product and Operations to help the company make the most informed decisions using data. Our team collaborates on high-impact projects across the company — from driving quality and operational efficiency to market analysis and rider satisfaction scores — we help to safely and efficiently scale the Waymo Driver. We are data-driven, curious, open-minded, and adapt quickly to new information.
In this hybrid role, you will report to a Staff Product Data Scientist.
You will:
- Define the science roadmap for Waymo’s marketplace experimentation platform
- Develop advanced testing methodologies to solve for physical-world dynamics like network effects and spatial-temporal correlations
- Establish rigorous best practices for experiment design and evaluation across the broader product organization
- Partner with engineering to translate algorithmic logic into automated, production-grade pipelines
- Act as the primary domain expert on causal inference, providing technical leadership and translating complex results into clear product strategy
You have:
- An advanced degree in a quantitative field (e.g., Statistics, Economics, Operations Research, Computer Science)
- 8+ years of industry experience with a deep focus on causal inference, experimental design, and applied statistics
- Proficiency in SQL and Python, with a track record of partnering with engineering to build automated experimentation tools
- Strong product sense and the ability to explain technical concepts to non-technical stakeholders
We prefer:
- Experience with two-sided marketplaces and physical-world operations (e.g., ride-hailing, delivery)
- Familiarity with core marketplace systems (e.g., pricing, matching)
- Experience integrating algorithmic methods into large-scale internal platforms
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, and skill level. Your recruiter can share more about the specific salary range for the role location or, if the role can be performed remote, the specific salary range for your preferred location, during the hiring process.
Waymo employees are also eligible to participate in Waymo’s discretionary annual bonus program, equity incentive plan, and generous Company benefits program, subject to eligibility requirements.
How this employer is doing
solid
- News: Growing or Expanding
- H1B: Active Visa Sponsor
- Expanding
- Active Visa Sponsor
In the news
'I feel safer around a Waymo.' Expansion of autonomous robotaxi service has supporters cheering, Los Angeles Times
Pay for this role
$230,000 to $284,000 per year
That is the employer's posted range, and where you land in it is usually decided in one conversation. Before that conversation, run the numbers: analyze an offer for this role.
Before you apply, worth reading
How JobMinglr reads this job
Every listing here is scored against your profile before you apply: skills overlap, experience level, location and work arrangement, each weighted and explained. You see the score and the reasons, not just a list. How the matching works.