Six Figure Work

Senior Business Intelligence Analyst

Waymo

Company websitewaymo.com (Waymo, opens in new tab)

Base salary $168K  to $207K

Employer-published annual base salary, USD. Advertised base range in San Francisco, CA +1 more

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  • LocationSan Francisco, CA +1 more
  • WorkplaceWorkplace not stated
  • Status at last checkSource accepting applications when checked
  • Last checked (1 h ago) · observed since
All places named
  • San Francisco, CA
  • Mountain View, CA USA

About this job

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.

This role follows a hybrid work schedule and you will report to the Manager of Product Data Science.

You will:

  • Mine, triage, and analyze data from disparate, large-scale sources to extract insights that help evaluate driving scenarios and support onboard release deployment
  • Partner with Product Managers, Engineers, Program Managers to identify the right measurements for product performance and prioritization
  • Design and implement foundational data pipelines, and build the right reports and visualizations to drive insights
  • Develop a deep understanding of various metrics, datasets, and data sources in relation to self-driving vehicle releases and the product roadmap
  • Organize, develop, and contribute to signals and heuristics that capture targeted driving behaviors and scenarios
  • Drive a culture of excellence and help establish best practices within the broader data science team

You have:

  • 5+ years of experience in a related technical field (or equivalent practical experience), with a proven track record of managing stakeholder relationships and prioritizing multiple projects
  • Ability to scope, structure, and solve ambiguous problems from end to end by creating clear analysis plans
  • Strong data intuition and statistical knowledge, with the ability to translate disparate signals from large, diverse datasets into insights on vehicle behavior
  • Coding experience with SQL to design and implement complex data pipelines following best practices
  • Strong attention to detail

We prefer:

  • Experience in the Autonomous Vehicle industry or a strong background in engineering or physics

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. 

Salary Range

$168,000—$207,000 USD

Source: Waymo on Greenhouse · View original posting (opens in new tab)

Pay in context

This role's base floor ($168,000) is above 31% of the 1,514 Data & ML roles in California listed on this site; 9 others list the same floor. Their median floor is $187,500; the middle half runs from $159,200 to $229,375.

Only jobs on this site count, and each one publishes a base salary of $100,000 or more, so this compares six-figure jobs with each other, not with the whole market. Computed Nov 7, 2026.

This range next to 6 other live Waymo roles with the nearest advertised base floor
Chart as a table
This range next to 6 other live Waymo roles with the nearest advertised base floor
RolePublished base
Senior Business Intelligence Analyst (this listing)$168K - $207K
Data Scientist$170K - $216K
Field Safety Engineer$170K - $210K
Senior Android Platform Engineer$170K - $216K
Software Engineer, Vehicle Platforms C++$170K - $216K
Machine Learning Engineer, Perception, Vision-Language Models$170K - $216K
Senior Safety Management System (SMS) Analytics Specialist$168K - $207K

Same $100K to $400K scale as every card. All Waymo roles · How to read the bar

Observed changes

  1. First observed on the employer's board
  2. Began meeting the published-salary criteria
Observed since
Employer-stated posting date
2026-06-02
Where this pay comes from

Location as the employer wrote it: Mountain View, CA USA ; San Francisco, CA, USA

$168,000—$207,000 USD

Method
Employer text, read with fixed rules and re-verified
Checked
Rule set
us-base-v2

The pay passage appears in the employer's own job text. Fixed, deterministic rules located it, and the passage below was checked against the stored copy of the posting.

What we verified

  • The pay figures come from the employer's own listing, quoted exactly above.
  • The pay is an annual base salary in US dollars with a minimum of at least $100,000.
  • The role was publicly listed on the employer's job board when last checked.

We do not verify what the employer will actually offer, whether the employer is still recruiting for the role, or anything beyond what the employer published. Full methodology.