Data Science Intern applicants have rated the interview process at Spotify with 2.9 out of 5 (where 5 is the highest level of difficulty) and assessed their interview experience as 63% positive. To compare, the company-average is 47.4% positive. This is according to Glassdoor user ratings.
Candidates applying for Data Science Intern roles take an average of 13 days to get hired, when considering 8 user submitted interviews for this role. To compare, the hiring process at Spotify overall takes an average of 39 days.
Common stages of the interview process at Spotify as a Data Science Intern according to 8 Glassdoor interviews include:
Phone interview: 29%
One on one interview: 19%
Skills test: 14%
Group panel interview: 10%
Personality test: 10%
Drug test: 5%
IQ intelligence test: 5%
Presentation: 5%
Other: 5%
Here are the most commonly searched roles for interview reports -
I applied through a recruiter. I interviewed at Spotify (Toronto, ON) in Jan 2024
Interview
Interview process was a phone call that went terrific with a recruiter, followed up by a technical screening a few weeks later. Finally, there is at least one or two rounds with the Senior Manager of the team.
Interview questions [1]
Question 1
Data is all related to Spotify, 2 Easy Python questions related to basic pandas queries. 2 SQL Easy/Mid questions relating to joins and aggregate functions, and 1 SQL Hard question asking to do a complicated ranking and filtering based on numerous factors.
The interviewers seemed to be in the bad mood, maybe from overwork due to recent layoffs. Nevertheless, the questions were not difficult but the lack of enthusiasm from the panel made the process extremely tedious.
Had an online phone screening with the interviewer but was experiencing a lot of technical difficulties over the phone. She went over the program and then asked a few questions.
The process was described as phone screening then 2 more interviews: technical and then, behavioral. I had not passed the phone screening which I thought went pretty well despite the technical difficulties (Had to move the call onto Teams)
Two interviews, one with engineers about technical stuff, one with manager about general skills. They were friendly, especially the manager. Technical interview included questions about ML and data science, plus some coding challenges.