Practice real data science interviews tuned by the interviewers who actually run them.

Netflix's primary engagement metric has dropped 20% week-over-week. Leadership is alarmed and wants a root cause analysis within 48 hours. The drop could be a data issue, a seasonal effect, a product change, a content gap, or a genuine shift in user behavior. You need to structure a systematic investigation and determine what's real vs. artifactual.

Netflix's recommendation engine drives 80% of content played on the platform, but leadership wants to understand whether it's truly successful or just convenient. The team debates whether click-through rate, completion rate, or long-term retention lift is the right north star. You need to define a rigorous success framework, handle the tension between 'good enough' recommendations and genuinely great ones, and design an experiment to test a new algorithm.

You are the PM for the Netflix homepage. Leadership asks: 'Is the homepage successful?' The challenge is disentangling homepage performance from overall Netflix performance. The homepage has recently been redesigned with larger hero content and fewer visible rows, and there's a debate about whether faster time-to-play or deeper browsing is the better outcome.

Netflix is launching a new personalized row labeled 'Because you watched [title]' to improve content discovery. The team needs a single North Star metric for discovery quality AND explicit anti-gaming constraints to ensure the metric reflects genuine discovery rather than inflated engagement. The previous row iteration increased play starts but not watch-through — a red flag for metric inflation.

Netflix historically offered a 30-day free trial to new users, but recently eliminated it in many markets. Leadership wants to understand: was the free trial actually effective, and was removing it the right call? You need to define how you'd measure trial effectiveness, detect trial abuse, compare trial lengths, and evaluate the removal decision retroactively.

Netflix is testing a new trailer autoplay behavior on title cards — when users hover for 2 seconds, a 30-second trailer starts playing. The test shows higher play starts but unchanged total watch time. The team is split on whether this is a real UX improvement that helps users discover content faster, or metric inflation that makes the dashboard look better without creating real value.

Netflix has invested $17B in original content and needs a rigorous framework for measuring the performance of Netflix Originals. The challenge is that Originals serve multiple purposes — driving subscriptions, reducing churn, building brand, and filling catalog gaps. A simple viewership metric misses most of the value. You need to build a framework that informs renewal vs. cancellation decisions.

One million Netflix users have been inactive for six months — they're paying subscribers who haven't watched anything. Product and marketing teams want to re-engage them, but finance questions whether it's worth the investment. You need to segment these users, design a reactivation strategy, measure its effectiveness, and determine when the cost of reactivation isn't worth it.