Real, anonymous reports from people who interviewed for Data Scientist at Amazon, newest first and distilled into what to expect across the loop.
I started with an HR call, and then the process moved into two technical interviews. The first phone screen was with a data scientist for about an hour, with a mix of coding and applied ML theory. I remember getting two coding prompts—one focused on SQL and another on algorithms—and then they bounced into ML basics in between. The biggest moment that threw me was when I gave a hand-wavy answer; the interviewer didn’t let it go and kept pushing until I got more precise and actually talked through my thinking.
My path started with an online assessment centered on SQL, followed by a screen interview that focused on ML basics. From there it escalated to an on-site with five separate interviews, so I got a lot of different “angles” on the role in one long stretch. The technical content spanned coding, ML breadth, and ML depth, and the questions were paired with leadership-principle prompts in each session.
The interview process typically starts with an HR call, followed by a technical phone screen, and culminates in a structured on-site loop consisting of multiple rounds, often five or more, covering various topics. Candidates noted the importance of understanding the flow and expectations at each stage to prepare effectively.
Candidates can expect a strong emphasis on technical skills, particularly in SQL, machine learning concepts, and coding exercises. Interviews often include practical problem-solving tasks and require candidates to demonstrate depth in their technical understanding and reasoning.
Behavioral questions are integrated throughout the interview process, heavily tied to Amazon's leadership principles. Candidates should prepare to discuss their past experiences in a structured manner, using the STAR method to illustrate their decision-making and impact.
Interviewers expect candidates to not only know concepts but also to apply them in practical scenarios, such as discussing modeling trade-offs or evaluating results. Candidates should be prepared to explain their thought processes and decisions in detail.
The overall interview experience is described as intense and demanding, with a focus on evaluating how candidates think under pressure. Many candidates reported that the difficulty was not just in individual questions but in maintaining clarity and consistency throughout the process.
Candidates often leave the interview process without an offer, feeling that the reasons are sometimes internal rather than performance-related. Many expressed frustration with the lack of closure or clarity on their performance despite feeling they had demonstrated their skills adequately.