Pros
QB is simply at the top of the field when it comes to real-world data science. I recommend working here for any data scientist who is optimizing for growth and learning (both in terms of technical skills and generalist skills). As a part of McKinsey with a unique culture, I love the community of QB data scientists who are still very tight-knit despite sprawling over many time zones!
Cons
This is both a pro and a con: as a client-facing data scientist, you will work extensively with non-technical McKinsey consultants and partners. This can be great to developing "both sides of your brain", as you need to get really good at communication for a non-technical audience. However, it can be quite frustrating at times because leadership doesn't always understand what data science is or what data scientists can do (their imagination can sometimes be stuck in the "business analyst world", even though they say they want advanced analytics). I think this is changing/getting better, but whenever things have been frustrating on a project it has tended to come out of a disconnect between the consultant and data scientist worlds on a project.