Having worked with some such folks in a quant-focused field, I can say that their performance was no better than average and in some cases worse. After a few hires like this, my boss actually pulled me aside and asked me to take over one of the main hiring projects because he and a few other managers were unhappy with the way the emphasis on this type of paper credential had failed to produce good enough analysts, and they wanted a process more focused on probing someone&#x27;s experience and ingenuity. I didn&#x27;t enjoy it at the time, but that 9-month project focused on that team&#x27;s hiring needs (which took me away from some of my technical projects for more time than I liked) ended up teaching me a ton about what candidates in general look like (at least for that type of firm).<p>But I grant this is reasoning just from the anecdata that I have. I can believe that <i>winners</i> perhaps represent a higher degree of skill, but then we&#x27;re talking about an extremely small number of people.<p>Generally you&#x27;re facing a tradeoff where you have to choose between a sort of rustic self-reliance skill set versus a bookworm skill set. People from either group can learn the other over time, but you can&#x27;t predict how well by testing them solely on trivia that constitutes their current main group. My preference is to hire for self-reliance and learn bookworm stuff later. I used to believe the opposite (e.g. hire someone good at math because they can always learn to be an effective programmer later) but my job experience made me believe the opposite (e.g. actually it&#x27;s pretty easy to teach people stochastic processes, machine learning, or cryptography, but it&#x27;s incredibly hard to teach people how to be good at creative software design).