Job brief: Staff Product Data Scientist, Marketplace ML

What JoRoute checked · Checked by JoRoute

• Listed on Waymo's own job board. JoRoute does not take listings from job ads or recruiters.
• First seen by JoRoute 2026-11-04 (2 days ago); last confirmed on the board 2026-11-06.
• The apply link opens careers.withwaymo.com, the address Waymo's board gives for this job.
• No other listing with this title and place on this board in the last 90 days.
• No layoff notices (WARN) under this name in the state files JoRoute reads.

What the listing says · Employer's own words, not checked

• Pay: $230,000 to $284,000 a year
• Job type: Not stated
• Where: Mountain View, CA, USA; San Francisco, CA, USA · Mountain View (US-MTV-EMF690) · San Francisco (US-SFO-MKT555)
• Posted: 2026-10-30

What the job asks · Employer's own words, not checked

Level: Lead / staff. The title says "Staff".

Must have

• 8+ years of industry experience applying ML to production problems

Conditions

• This role follows a hybrid work schedule and you will report to a Product Data Science Lead

Main duties

• Partner with Engineering, Product, and Data Science to build ML models that improve the efficiency of Waymo's marketplace
• Build models that predict conversion, wait times, and retention, and estimate the value of a vehicle in different positions
• Apply forecasting models for demand and supply time series
• Develop novel reinforcement learning models that continuously tune pricing, matching, and positioning parameters
• Design, run, and evaluate experiments for new models

Lines copied from the posting, not rewritten. "Preferred" or "nice to have" items are not listed as must-haves.

How it compares · Compared by JoRoute from listings

• Typical listed pay for data and analytics jobs in San Francisco, CA: $172k a year (146 listings, 27 employers). This listing is 50% higher.
• Across Waymo's 313 open listings, 52% of those with a posting date were first posted more than 60 days ago. How Waymo hires

What nobody outside the employer knows · Not known

• Whether the role is already filled or on hold: employers often leave listings up.
• How many people applied, and who reads the applications.
• Where in the published range an offer would land.

Ask before you apply

1. Which of the listed places is this role based in?
2. What are the interview steps, and when should I expect to hear back?

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Next steps

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