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.

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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.

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In this internship, you’ll:

• Partner with Data Science, Engineering, Product and Operations teams to improve supply efficiency and accelerate Waymo’s growth.
• Build sophisticated ML models and use causal methods to understand and forecast fleet conditions and rider behavior.
• Have the opportunity to deploy your work into our production systems to enable continuous decision making.

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At a minimum we’d like you to have:

• Actively in pursuit of Masters Degree in a quantitative field.
• Hands-on experience coding experience with Python and SQL.
• Statistics and Machine Learning knowledge.
• Ability to structure and solve ambiguous problems.
• Demonstrated experience communicating and collaborating with different stakeholders.

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It’s preferred if you have:

• Experience in supply optimization modeling and implementation (e.g. solver packages) and/or causal inference methods (e.g. causal forests, DoubleML, propensity matching).
• Demonstrated proficiency of Python/SQL/R data analysis libraries and packages.
• In pursuit of PhD in a Quantitative field

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General Perks

• Help solve challenging problems with a direct impact on the company
• Competitive compensation packages with a housing/relocation bonus (if applicable)
• Medical, dental, and vision insurance
• Fun intern events and networking opportunities

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Onsite Perks (These perks will only be applicable if the internship is on site)

• Free breakfast, lunch, dinner, and snacks
• Free access to Google shuttles
• Onsite gym

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