Hi All,
Thank you all for guiding me through Pair Programming Round. I was able to pass it.
I would appreciate if you could provide any insights or guidance on what type of questions might be asked in the next round that is : Virtual Problem Solving Case + Personal Experience Interview ? and any specific method or tricks to approach those questions.
Also will it be traditional Case Study round or is it more domain specific since it Quantum Black?
Thanks in advance.
Congrats on passing the Pair Programming round!
As for your next round, the best way to get concrete details is by reaching out to the recruitier. That being said, the case usually follows the typical business case format, but the interviewer may incorporate data-heavy or analytics-driven elements. So expect something like "a client has X problem" and you need to break it down structurally, but the solution will lean technical rather than pure business strategy.
The McKinsey PEI is actually quite well-understood, and the firm publicizes the types of questions and characteristics they'll be asking on their website: https://www.mckinsey.com/careers/interviewing (under PEI). That doesn't mean it's easy, and the best way to prepare is to sit down for an afternoon and brainstorm situations you could use for each of these cases, then write down every detail you remember. The good thing about PEI is that anyone can help you refine those stories! Have a friend listen to your story and check whether 1) it answers the question, 2) it was clear what you specifically did, and 3) if it positions you well as a coworker.
Best of luck!
Congrats!
Regarding your last question, on whether the case will be QB-specific or generic, do ask the recruiter directly. They're best positioned to tell you.
On the personal fit, read the guide that McKinsey sent you and you might also want to consider this targeted PEI course I've built which lots of candidates are finding useful:
• • Video Course: Master the McKinsey PEI
Best,
Cristian
hey Rid :)
great job!!! The next round is usually a mix but still very close to classic consulting style. the problem solving case is typically structured thinking plus some data interpretation, sometimes a bit more technical or product focused, but not deep coding. think along the lines of how you break down a problem, work with ambiguous data, and communicate clearly. it’s not a pure SWE interview.
the personal experience part is standard McKinsey, so expect stories on leadership, impact, and handling challenges, they go quite deep on your examples so be very structured and specific.
best prep is to practice normal cases, be sharp on interpreting charts, and have 2–3 strong stories ready that you can really defend in detail.
best,
Alessa :)
Congrats on clearing pair programming, that is the harder gate at QuantumBlack.
The Virtual Problem Solving Case is like a standard McKinsey case but with a data and AI lean. Expect problems around ML, AI, or data transformation, like building a recommendation engine, reducing churn with predictive models, or deploying computer vision. Same structure as a classic case, just more technical content.
A few things to prep.
Know how ML models are built and deployed end to end. Data collection, feature engineering, model selection, validation, deployment, monitoring. You do not need to code, but speak the language confidently.
Be ready for trade-offs. Accuracy vs interpretability, build vs buy, cloud vs on-prem, rules vs ML.
Prep sizing and math around data products. For example, the ROI of a churn model or the cost of a data platform.
On PEI, it is standard McKinsey. Three stories, Personal Impact, Entrepreneurial Drive, Inclusive Leadership. Use STAR, be specific, and each story needs a clear you moment, not a team moment. At least one should show technical or analytical leadership.
Good luck.
Hi Rid,
Hope you are doing good!
My McKinsey Initial Round - PSS PEI Connection Interview for Software Engineer is scheduled and If you completed this round, can you please share like what to expect in this round and how was your experience.
I would absolutely expect it to be more domain specific (but check with them). PEI is the classic McKinsey PEI
