I went through McKinsey's PM loop for a role on their Lilli product team (their internal AI assistant) earlier this year. Here's what the interview actually looked like, not the generic 'design a product for X' stuff you'll read elsewhere.
Background: I'm a senior PM with seven years in B2B SaaS. McKinsey's PM hiring is pretty specific: they want people comfortable working inside a consulting context, where 'the user' is often a consultant, and where speed and trust are everything.
The loop: recruiter screen, one PM skills round, one strategic round, one behavioral, and a final with a partner. Four rounds total, spread over about three weeks.
PM skills round: this felt closest to a traditional PM interview. Questions included: 'How would you prioritize features for an internal tool where you have direct feedback from 1,000 consultants but you also have leadership asking for enterprise features?' 'Tell me about a product decision you made with incomplete data.' They pushed on what 'incomplete' meant and how I weighted the gaps. 'How do you measure success for a feature that's hard to A/B test?'
Notably: no 'how many golf balls fit in a school bus' type questions. They're not doing estimation puzzles.
Strategic round: more about external context. Where do you see AI impacting professional services over the next three years? What's the risk McKinsey's internal tools team faces from external vendors? They want to see that you can zoom out.
Behavioral: standard STAR. Very similar to what consultant_cam wrote in the other thread here: influence, failure, data-driven decisions.
Comp: the PM offer I got was in the $180K-$210K range depending on level, with a performance bonus structure that's different from typical SaaS PM comps. No RSUs in the traditional sense since it's a private partnership.
The culture was collegial, high-trust. They move fast if you're in the funnel. The Lilli team in particular felt like a startup inside a large institution, which suited me.