Applied Scientist applicants have rated the interview process at Amazon with 3.3 out of 5 (where 5 is the highest level of difficulty) and assessed their interview experience as 75% positive. To compare, the company-average is 58.2% positive. This is according to Glassdoor user ratings.
Candidates applying for Applied Scientist roles take an average of 21 days to get hired, when considering 4 user submitted interviews for this role. To compare, the hiring process at Amazon overall takes an average of 31 days.
Common stages of the interview process at Amazon as a Applied Scientist according to 4 Glassdoor interviews include:
Skills test: 33%
Phone interview: 33%
One on one interview: 33%
Here are the most commonly searched roles for interview reports -
One phone screen + an onsite with 4 technical interviews. The phone screen touches on some coding elements, simple data structure that are relevant to machine learning. The onsite interviews comprise of 1 coding interview and 3 ML interviews, covering topics from ML basics, predictive modeling, generative modeling, how to formulate and find data under hypothetically practical constraints. All are pretty easy. All interviews spend 1/2 of the time on the leadership principles.
Interview questions [1]
Question 1
ML basics, predictive modeling, generative modeling, etc.
I applied through a recruiter. I interviewed at Amazon in Apr 2020
Interview
The interview process was very structured. There were 3 rounds of interview. The first round was HR, the second was coding, and the final was onsite for 7 hours. The presentation itself had two sections. I presented my research work in the first part and in the second part I was asked to read a paper called Deferred Neural Rendering. It took me 2-3 days to prepare the presentation. I think I did decently well in the presentation part. The call dropped a number of times because of issues with Chrome or the internet.
I applied online. I interviewed at Amazon (Seattle, WA) in Dec 2020
Interview
Inter position interview; machine learning general question(overfitting, dropout) and simple coding(list duplicate items detection) wasn't hard enough to answer all questions. Some behavioral questions asking about the responsibility and limitations
Interview questions [1]
Question 1
what is dropout and overfitting? how can we solve?