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 interns partner with leaders in the industry on projects that create impact to the company. We believe learning is a two-way street: applying your knowledge while providing you with opportunities to expand your skill-set. Interns are an important part of our culture and our recruiting pipeline. Join us at Waymo for a fun and rewarding internship!

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You will:

• Create innovative statistical and machine learning methods and practical guidelines for assessing early software versions, prioritizing actionable insights and efficient evaluation
• Develop tools that pinpoint meaningful driving behavior changes resulting from even minor code modifications to major ML model updates, effectively guiding engineer's focus to the signals among noise
• Validate your methodology and provide code to enable ongoing use of your methodology (by leveraging the Alphabet software development infrastructure)
• Present findings to stakeholders

You have:

• Defining reasonable and useful statistical models for a given data set/ data generation process
• Rigorous application of inferential statistical techniques, especially estimation, sampling theory, and confidence intervals
• Familiarity with modern applied statistical methods, their assumptions, and when to use them
• Be proficient in coding in Python, with an emphasis on statistical coding, data manipulation, and data visualization: also have basic knowledge of SQL
• Effective communication via presentations and/or written documentation

We prefer:

• Appropriately balance technical/ Mathematical complexity and practical considerations within the data or problem context
• Good time/ project management skills
• Fluency in SQL

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