Why do mathematicians earn more than statisticians?

well... you need to look down another paragraph or two. 'job prospects'.

There are over 10x statistician positions vs mathematicians. In modern capitalism, pay rate for a given position is roughly related to the expected ROI, adjusted by the supply and demand. There's an assload of demanding statistics work, a lot of it has very explicit value to a given company, but there's also a fairly large number of competent statisticians, and (I imagine) a fairly robust hiring process and headhunter network to keep those positions supplied with good talent. If HR sucks at finding good talent, then keeping good talent becomes a priority, meaning pay increases.

Mathematicians on the other hand... what kind of business process demands algebraic topology or something as an integral part of their process? There are certainly roles in industries dealing heavily in graph optimization problems (for one example I know a little about... transit companies for example) but there are a very small number of roles like that. Because they're small though, and because there's no clear path to find talented individuals, and no efforts to train them, I imagine it's a giant pain in the ass to find someone qualified. I'm a coder, and it's really hard even to find good software engineers. There's like a million of them out there, literally, huge networks training software engineers, huge infrastructure in place to train software engineers, huge networks in place to identify and hire good software engineers, and corporations still suck at it. The estimated difference between a 'good' coder and a bad one is something like 10x productivity... it's massive, but most coders kind of suck. You get by by having enough coders that your heroes can carry your dead weight hopefully.

Now. Imagine a company that doesn't need 'an engineer'. There are no schools that have prepared people to work for your use case. You may as well be looking for a daoist master, for all you know of their art, or even where to find one. There are a tiny, tiny number of people in the world potentially that can be a proper rock star given your needs... in the rare event you find one, you damn well better keep them happy.

That said... by this estimate, there are under 4,000 mathematician jobs in industry (or whatever that number represents). Here's a far better question... how many mathematicians are there total that are qualified for such a role? Over 4,000? Over 10,000? 50,000? Getting an industry job as a math major may well be like winning the lotto (you get lucky with network) or it might be highly dependent on your also having a very advanced skillset in another area (coding).

From a statisticians perspective... E[math degree] > E[statisticians degree]? E[math degree value] = P(math hiring)E[income] = P(hiring)$105,810 E[statistician degree value] = P(stats hiring)$80,500.

in other words, if your personal chance of getting hired as a statistician is more than 31% higher than your chance to find employment as a mathematician, then you're better off pursuing stats, even though the median income is lower. That radically changes though if you count machine learning as stats and you decide to gun for a job as an ML engineer, there are some crazy salaries there, haha.

Given the radically higher number of stats jobs though, I think it's pretty clear which degree is more commercially valuable.

/r/math Thread