Went through Discord's DS interview loop in late 2025 and early 2026 for a role on their product analytics team. Here's exactly what the process looked like and what they tested.
Process overview: Recruiter screen, HM call, then a 4-round virtual onsite. No take-home for this DS role (apparently some teams do have one, so clarify with your recruiter).
SQL round: Hands down the most technically demanding SQL I've had in a consumer company interview. It wasn't just "write a query to find users who did X." They gave me a realistic schema with events tables, user tables, server membership data, that kind of thing, and asked me to answer a business question. One of the prompts was something like: find the top servers by 30-day retention of new users who joined in the last quarter, and then identify if there's a difference in retention by server category. That requires window functions, multiple CTEs, conditional aggregation. Not beginner stuff. Know your window functions cold.
Stats / probability round: Standard DS interview territory but they went deeper than most. Topics that came up: A/B testing and when to use one-sided vs two-sided tests, power analysis basics (they wanted to know if I understood why sample size matters before running an experiment), Simpson's paradox (they had a real example from their data framing), and one bayesian probability question that was more of a thought exercise than a computation.
Case study / product analytics round: This is the one that felt most Discord-specific. They gave me a scenario: a community feature's DAU dropped 15% week over week. Walk them through your investigation. The right move is to break it down systematically: is it real or a tracking issue, is it global or segment-specific, new users vs. retained users, any recent product changes or infrastructure incidents. I found this round more interesting than a standard case because the product surface (communities, servers, voice channels) is rich enough to reason about genuinely.
Behavioral / cross-functional round: Standard senior DS stuff: how do you communicate findings to PMs who disagree with your analysis, have you killed a project based on data, how do you work when you don't have clean data. They care about influence and stakeholder work, not just technical execution.
Comp context: For a mid-to-senior DS role (L5 equivalent internally), I've seen ranges around 200-240k TC in remote/SF depending on the team. A friend who joined last year is on the growth analytics team and mentioned her package was at the lower end of that because it was partially equity-heavy and Discord is pre-IPO.
Bottom line: If your SQL is rusty, that's where to focus first. The stats round is fair. The product case is the most fun and the most differentiated.