Data Scientist Intern applicants have rated the interview process at Amazon with 3.2 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 57.5% positive. This is according to Glassdoor user ratings.
Candidates applying for Data Scientist Intern roles take an average of 29 days to get hired, when considering 36 user submitted interviews for this role. To compare, the hiring process at Amazon overall takes an average of 28 days.
Common stages of the interview process at Amazon as a Data Scientist Intern according to 36 Glassdoor interviews include:
One on one interview: 22%
Skills test: 22%
Phone interview: 14%
Personality test: 12%
Presentation: 12%
Background check: 6%
IQ intelligence test: 4%
Group panel interview: 4%
Drug test: 2%
Other: 2%
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Asked questions about regressions (mostly linear and logistic). Had questions on fraud detection, loan defaults, etc. The interviewers were to the point and helped me with the process to get to answers. Overall, it was great.
There were two back-to-back rounds: one hour of behavioral questions focused on leadership principles, 30 minutes on statistics and machine learning, one SQL histogram question, and one Python question for 30 minutes.
I had 2 rounds of interview. One was behavioural based on leadership principles + coding round based on DSA and the second round was technical focussing on Data science and ML fundamentals.
Interview questions [1]
Question 1
Explain the end - to - end data processing pipeline.
I applied through an employee referral. The process took 4 weeks. I interviewed at Amazon (Seattle, WA)
Interview
1) Recruiter call
2) 2 rounds of each 1 hour technical questions + Behavior questions
1) Technical: Coding with SQL, and Pandas
2) Behaviour: Amazon Principal
3) Confusion matrix -- very detailed, you need to know what you saying
Interview questions [1]
Question 1
1) Technical: Coding with SQL, and Pandas
2) Behaviour: Amazon Principal
3) Confusion matrix -- very detailed, you need to know what you saying