Totally agree with this. I will have (soon) my master's and not a PhD, but even then I have been trying to figure out what my value is in the workplace. I've found it coming into play in very surprising ways. That is to say, I've surprised myself at how valuable my "math" skills are in areas that seem to have nothing to do with mathematics, and thankfully, my employer is also recognizing this as well.Here's an interesting blog perspective on the state of Math PhD in today's workforce:
I always sensed a vague snobbery towards stats and computer science from the so-called pure math community, which I think needs to die.I too largely agree with the blog perspective. It is certainly true that there is a much more limited number of academic jobs available for all PhD graduates, including math PhDs, but the training that math MS or PhD graduates in particular receive is of increasing importance in a wide range of careers, and not just in finance, security, or statistics/data science.
It is interesting to note how the blog post states that 'We should not push students into applied math and statistics courses or make them into “data scientists”'. I disagree somewhat with this assessment. While I wouldn't state that math students should be pushed into these courses, I do think that undergraduate math students should be strongly encouraged (or required) to include some applied math and statistics courses (along with programming courses) as part of their curriculum, for the following reasons:
1. I think it is important for math students at the undergraduate level to get a sense of the breadth and range of the mathematical sciences as a whole, and how the different areas of mathematics connect to each other. In this respect, having students take a few applied math or statistics courses would broaden the level of understanding in how math connects to the world.
2. In general, it is important for all students to gain a broad range of marketable skills which can complement their education. Including programming or CS courses, along with applied math or statistics courses, in the curriculum is a relatively painless way for math students to gain precisely these type of marketable skills.
I agree with you that there is a certain snobbery towards "applied" fields such as statistics, computer science, or applied math from the "pure math" community -- attitudes that are unhelpful and should die out.I always sensed a vague snobbery towards stats and computer science from the so-called pure math community, which I think needs to die.
As far as how mathematicians work and what they do, I think the line between pure and applied math will always be there and is in some sense necessary. The work that many mathematicians do involves following a line of questioning that can take them well out of any practical realm, and while these can and do filter back into applied fields, we should not insist that they must do so. Some of my favorite fields of math will probably never, ever,ever,ever have any "real world" use but are so delightful to work with that I just don't care. (I'm thinking specifically of large cardinals here and some really foundational mathematical logic stuff).I agree with you that there is a certain snobbery towards "applied" fields such as statistics, computer science, or applied math from the "pure math" community -- attitudes that are unhelpful and should die out.
I would also add that, in my own humble opinion, the line between pure and applied mathematics is artificial and arbitrary. Much research in pure math has spawned applications (e.g. number theory in cryptography, mathematical logic in computer science, more recently algebraic topology in statistics/data science) and developments in what is generally accepted in applied math (e.g. differential equations, dynamical systems, mathematical physics) have subsequently influenced developments in various branches of pure math.