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McKinsey - QuantHub assessment

Hello, 

 

I will be performing the QuantHub test by Mckinsey. Has anyone done it recently and could share their thoughts on what is actually being tested? Additionally, please let me know if you know about any practice tests for it.

 

Many thanks!

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Evelina
Coach
on Sep 16, 2025
EY-Parthenon l Coached 100+ candidates into MBB & Tier-2 l 10% off first session l LBS graduate

Hi there,

QuantHub is McKinsey’s newer online math and data reasoning screen. It’s quite different from Solve—it’s more like a numerical reasoning / GMAT quant drill. 

  • Content tested:
    • Basic arithmetic (percentages, ratios, growth rates).
    • Word problems (profitability, averages, weighted means).
    • Data sufficiency / quick logic checks.
    • Interpreting short tables, graphs, or charts.
  • Format: Timed, adaptive multiple-choice questions. Difficulty ramps up depending on how you’re performing.
  • Skills assessed: Accuracy under time pressure, ability to reason logically, and efficiency with calculations.

Preparation tips:

  • Practice GMAT Problem Solving and Data Sufficiency questions.
  • Brush up on mental math—percent changes, fractions, approximations.
  • Work on SHL/assessment-style numerical reasoning tests for speed.
  • Keep scratch paper handy and organize calculations cleanly.

Best,
Evelina

Anonymous A
on Sep 17, 2025
From what I can see, the QuantHub test involves 3 sections:
- R coding.
- Python coding. This section includes NumPy and scikit questions.
- Statistics. This section includes T-tests, Anova regression distributions, and chi-square.

As such, it is not similar to the old PST, or has it changed?. Does anyone have any other information regarding the QuantHub test? Thank you.

Source: https://www.myconsultingoffer.org/case-study-interview-prep/mckinsey-quanthub-test/
Alessa
Coach
on Sep 17, 2025
xMcKinsey & Company | xBCG | xRB | >400 coachings

Hi there,

QuantHub for McKinsey is mostly a data analytics and reasoning test. Expect multiple-choice questions covering statistics, probability, data interpretation, and sometimes basic coding logic (but usually no heavy programming). It’s less about advanced math and more about interpreting data quickly and accurately under time pressure.

You won’t find many official practice tests, but you can prepare with GMAT-style quant, probability exercises, and online data interpretation sets. Brushing up on descriptive stats (mean, variance, distributions) and hypothesis testing basics also helps.

best, Alessa :)