Waymo Data Scientist Interview Questions + Guide in 2025

Waymo is at the forefront of autonomous driving technology, dedicated to becoming the most trusted driver and enhancing mobility while prioritizing safety.

As a Data Scientist at Waymo, you will play a crucial role in analyzing and interpreting complex datasets to enhance the reliability and performance of autonomous driving systems. Your key responsibilities will include developing evaluation frameworks for vehicle performance, creating metrics to assess driving quality, and utilizing advanced statistical models to derive actionable insights. Collaborating closely with engineering teams, you will address intricate cross-functional challenges and contribute to improving Waymo's data-driven decision-making processes. The ideal candidate will possess a strong background in quantitative fields, such as Computer Science, Robotics, or Statistics, along with proficiency in programming languages like Python and SQL. A passion for solving ambiguous problems, coupled with a keen interest in the intersection of data science and autonomous systems, will make you an ideal fit for this innovative environment.

This guide will equip you with the insights and knowledge needed to effectively navigate the interview process and showcase your alignment with Waymo's mission and values.

The interview process for a Data Scientist role at Waymo is structured to assess both technical and interpersonal skills, ensuring candidates align with the company's mission and values. The process typically consists of several key stages:

1. Application and Initial Screening

Candidates begin by submitting their application through Waymo's career page. After a few weeks, selected candidates are contacted by a recruiter for an initial screening. This 30-minute call focuses on understanding the candidate's background, skills, and motivations for applying to Waymo. The recruiter will also provide insights into the company culture and the specifics of the role.

2. Technical Assessment

Following the initial screening, candidates are required to complete a technical assessment, often conducted through platforms like HackerRank. This assessment typically includes questions on SQL, statistics, and data visualization. Candidates should be prepared to demonstrate their proficiency in data manipulation and analysis, as well as their ability to solve real-world problems using data.

3. Technical Interview

Candidates who successfully pass the technical assessment will move on to a technical interview, which lasts approximately 45 minutes. This interview is usually conducted via video call and involves a data scientist from the team. The focus will be on practical applications of data science, including coding exercises in Python or SQL, statistical analysis, and discussions around data interpretation. Candidates are encouraged to think aloud and treat the interview as a collaborative discussion.

4. Virtual Onsite Interview

The final stage of the interview process is a virtual onsite interview. This comprehensive round typically consists of multiple one-on-one interviews with various team members, including data scientists and engineering leads. Each interview lasts around 45 minutes and covers a range of topics, including advanced statistical methods, machine learning concepts, and problem-solving approaches. Candidates may also be asked to present their past projects and how they relate to the work at Waymo.

Throughout the process, candidates should be prepared for a mix of technical and behavioral questions, as well as discussions about their experiences and how they align with Waymo's goals.

Next, let's delve into the specific interview questions that candidates have encountered during this process.

Practice for the Waymo Data Scientist interview with these recently asked interview questions.