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From the point of view of someone hiring/interviewing/having spent some time around PhDs, I'd say the main benefit is that it pushes you to be intellectually more capable. In a good university, doing original research, you'll be doing a lot of actual thinking and continuous learning and be pushed to do more of it than you'd do naturally. This is the main reason I wish I had done a PhD, although I don't think I'm smart enough to have gotten in a good programme (graduated with a 2.2 in engineering from Cambridge - all the MIT/Princeton/Stanford/whatever admitted had firsts). It's in no way the sole predictor, but the probability of someone have done hard things and being able to solve tougher problems [1] quicker is higher with a PhD than someone who spent the same time in industry. It's also tremendously competitive (in the same way, say, Goldman Sachs is in "business") so you can trust the PhD admissions committee to have done some filtering for you. Finally, it takes a lot of willpower to stick through it til the end (particularly in the US with its much longer programs), and drive is a strong predictor of adding value to a company later. On the downside, few people in business realise that because they haven't hung around PhDs or thought about it much, and just see a "lack of industry experience", an "attitude" and "not the most commercial mindset" (usually with a mention of the "ivory tower"). A good corporate job will have you learn a lot (broader, less specialist, probably less hard); but most corporate jobs are not good, and pay well to compensate the drop in intellectual challenge and loss of skills that results vs your undergraduate self (although you'll pick up more useful soft skills, to an extent, vs learning to navigate bureaucracies which are the soft skills a PhD teaches you). I heard that across practically all academic fields. [1] Unfortunately most of the problems people actually need solved in tech companies, like building a data warehouse, some reporting, a user friendly front end, are not "tough problems" in the way, say, building a machine vision engine tailored to your specific industry might be. |