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Historical candidate account: this article preserves one person’s reported experience. The interview date was not recorded in the original text, and updating this page does not make the account a current hiring process. Names, levels, durations, questions, outcomes, and approximate compensation are as reported, not independently verified or endorsed by the employer. Confirm the current role and assessment with the recruiter.
Here is a Spotify data scientist interview case study.
Spotify Data Scientist interview summary
How it gets started: H.R. reached out on LinkedIn.
Job Level: Junior
Year of Experience: 1 -2 years
Degree: M.S. in Statistics
Offer: Yes
T.C.: ~200K USD
Location: New York City
Interview process: 5 weeks
Team: Personalization
Preparation: 2 months
Has a job: yes
Spotify Data Scientist interview round 1: recruiter call
Resume deep dive, favorite project, who are the stakeholders, and the most challenging part of the current job: whether it's more on the technical side or communication/sharing insights with stakeholders.
Spotify Data Scientist interview round 2: hiring manager informational call
Introduction of the team, making sure it will be a good fit based on the background.
Spotify Data Scientist interview round 3: technical screening
- Python or R: (20 minutes)
Given a data file, import it into the console, and create a new column derived from certain conditions from another column.
Follow up: write a function that you can call to replicate what you just did.
Run the code and make sure the results match.
- SQL
2 tables:
ab_testing
user_id | testing_bucket (treatment/control)
streaming
user_id | date | duration
- Open question: with the above date, what kind of analysis do you want to do?
- Write a query to compare the average streaming time between the two testing groups.
- What kind of statistical test (two-sample t-test) would you perform, and how would you explain the results to business stakeholders (non-technical)?
- Product sense
If a subgroup's streaming time increased significantly while another subgroup decreased, how would you analyze this, and how do you explain this to a business leader?
If we can't do ab testing, how do we know if a certain product feature is going to be useful and if we can quantify its impact?
Spotify Data Scientist interview Round 4: Takehome date challenge:
Given a set of popular editorial (manually curated by the music editorial team, not algorithmically generated) playlists and their followers' streaming data.
What kind of insights have you found? Anything we can do to improve the playlist or help the music editorial team?
Spotify Data Scientist interview final round: virtual onsite
- Director: mostly behavioral questions
- Product manager: past experience partnering with product managers, recommendations based on different scenarios, how to improve Spotify.
- Data scientist: basic machine learning, recommendation algorithm evaluation, cold start problem: launching a playlist in a new country, how do we know if this playlist should be included or featured on the homepage without enough customer data.
- Take home presentation to the whole team.
Spotify Data Scientist offer
Received the offer one week after the virtual onsite interview.
Define the experimental unit before averaging streaming time
The reported schema has assignments at user level and multiple streaming rows per user. Define the reporting window, aggregate streaming time to each assigned user, and retain assigned users with zero observed streaming when a complete event feed supports zero. Averaging raw streaming rows weights frequent streamers differently from averaging users. Select an uncertainty method appropriate to the user-level outcome and its distribution; a generic two-sample t-test is not automatically correct for every design. Investigate subgroup findings with the planned multiplicity strategy and avoid attributing observational playlist differences to curation alone.
Practice one reported prompt, state the data and assumptions, produce a checkable answer, and explain one limitation. Then change a condition and see whether your reasoning still holds. Use this related practice resource for a follow-up; it is separate from the historical interview report.
