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Spotify interview notes, page 1 of 2

Large Enterprises

Screna has 18 Spotify interview write-ups. The most reported round is the product sense round (10).

18 interview notes · updated Jul 2026

Spotify·Product Manager·Onsite - Product Sense / Strategy

Apr 2026
Spotify PM interview with a market expansion case focused on launching in South Africa. Pretty open-ended, which I wasn't fully prepared for.
  • How would you approach launching Spotify in South Africa?

“I jumped straight into user segmentation and kind of skipped over the 'why South Africa, why now' framing which probably would've landed better.”

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Spotify·Product Manager·Onsite - Product Sense / Strategy

Apr 2026
Spotify PM interview with a single product diagnosis question. Pretty focused session, no fluff, just one meaty scenario about debugging a user-facing issue.
  • You're a PM at Spotify. Walk me through how you'd diagnose a connection issue that users are reporting.

“I jumped straight into user segmentation and forgot to first clarify what 'connection issue' even meant.”

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Spotify·Product Manager·Onsite - Product Sense / Strategy

Apr 2026
Spotify PM interview, one question about measuring Discover Weekly. Not much else to go on but it was the kind of question that sounds straightforward until you're actually in it.
  • How would you measure the success of Spotify's Discover Weekly feature?

“I went straight for engagement metrics and kind of forgot about the bigger picture for a bit.”

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Spotify·Machine Learning Engineer·Technical Phone Screen

Apr 2026
Deep ML interview at Spotify for an MLE role, basically one long technical conversation about unsupervised clustering. No fluff, they went straight into the weeds and stayed there.
  • Walk me through K-Means: the objective function, how the algorithm works, and what can go wrong with it.
  • How do you choose the right value of k, and what evaluation methods would you use without any ground-truth labels?
  • Compare agglomerative and divisive hierarchical clustering. What do the different linkage criteria actually do, and what are the complexity tradeoffs?
  • Explain DBSCAN: how does it define clusters, what role do epsilon and minPts play, and where does it break down?
  • How does a Gaussian Mixture Model differ from K-Means, and how does EM actually fit the model?
  • When would you use spectral clustering over the other methods, and what's the computational cost you're accepting?

“Started fine with the sum-of-squared-distances objective and Lloyd's steps, but fumbled a bit explaining k-means++ initialization.”

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Spotify·Product Manager·Onsite - Product Sense / Strategy

Apr 2026
Spotify PM interview, one question in, product analytics case about a metric drop. Pretty standard format but the question had enough moving parts to trip you up if you weren't structured about it.
  • Song listens on Spotify dropped 25% recently. How would you diagnose what's going on?

“I went straight to segmentation before even clarifying the metric, which I think was a mistake.”

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Spotify·Machine Learning Engineer·Technical Phone Screen

Apr 2026
Spotify ML engineer interview that went deep on unsupervised learning. The whole session was basically one long question about clustering methods, which sounds manageable until you realize how many angles they want you to cover.
  • Walk through multiple unsupervised clustering approaches and compare them across dimensions like core intuition, cluster shape assumptions, hyperparameter selection, scalability, failure modes, evaluation without labels, and preprocessing for high-dimensional or sparse data.

“This was one question but it kept branching.”

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Spotify·Machine Learning Engineer·Onsite - System Design / Architecture

May 2026
Spotify ML Engineer interview focused entirely on a single deep-dive system design question about predicting free-to-premium user conversion. It was one of those rounds where they just pick one problem and go six layers deep on it, which I was not fully prepared for.
  • Design an end-to-end ML system to identify which free-tier users are most likely to convert to premium, covering problem framing, data, features, modeling choices, loss functions, and evaluation.

“This question ate the entire session.”

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Spotify·Data Scientist·Technical Phone Screen

May 2026
Interviewed at Spotify for a data science role. One question, pretty standard, but it's the kind of thing that sounds easy until you're actually in it.
  • Walk me through a data science project you've worked on.

“I had a project ready but rambled way too much on the setup and barely got to the results.”

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Spotify·Software Engineer·Technical Phone Screen

May 2026
Interviewed for a SWE role at Spotify and got a balanced tree problem. Not much else to say, it was pretty much a standard algorithms screen.
  • Solve a balanced tree problem.

“Classic tree question.”

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Spotify·Product Manager·Onsite - Product Sense / Strategy

May 2026
Spotify PM interview with a classic estimation question. Pretty standard stuff but the scale of Spotify makes it more interesting than your average back-of-napkin exercise.
  • Estimate the total bandwidth required to support Spotify's streaming platform.

“I started with monthly active users and worked down to concurrent listeners, which felt right.”

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