Rigorous performance evaluation of the Waymo Driver is a critical part of scaling our ride hailing service and achieving Waymo’s audacious goals. Waymo data scientists work hand-in-hand with engineering teams at each stage of the software development cycle, employing statistical models and developing metrics and measurement frameworks to ensure that the Waymo Driver meets our strict standards for safety, compliance, and driving and service quality. Autonomous driving with complex machine learning systems presents a new paradigm in data science: in addition to leveraging data collected on-road, we generate our own data using state-of-the-art simulation technology—resulting in denser signals and challenging new problems in estimation and experimental design.

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!

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

• Develop and optimize sim-based eval strategies for a high priority novel problem area
• 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:

• Pursuing a PhD in a quantitative field (e.g. Statistics, Mathematics, Physics, Engineering, Economics, Political Science)

• A solid statistical theory foundation
• Excellent data institution- you are able to quickly grasp data challenges, understand the statistical nuances, propose a strategy to solve those challenges, and implement a solution
• Proficiency in programming with Python with an emphasis on statistical coding, data manipulation, and data visualization; also basic knowledge of SQL
• Proven skills in effective communication through presentations and written documentation
• Excellent interpersonal skills

We prefer:

• Experience with developing statistical methodology, casual inference, multiple hypothesis testing, A/B experiments, sampling methods, and/or predictive modeling

• Experience with interpretation and evaluation of complex ML systems and/or foundation models
• 3+ years of experience in data wrangling, visualization and data-driven storytelling
• Fluency in SQL
• Industry experience

Note: This will be a hybrid onsite internship position. We will accept resumes on a rolling basis until the role is filled. To be in consideration for multiple roles, you will need to apply to each one individually - please apply to the top 3 roles you are interested in.