It is often echoed that mathematicians make excellent software engineers, and that their logic-adjacent work will translate efficiently into coding and designing.
I have found this to be almost universally untrue. I might even say the inverse is true.
While I and many of my peers have capacity to navigate the mathematical world, it certainly is not what sets us (at least me) apart when designing clever algorithms and software tricks.
Point being: I dont think the property/trait that makes good programmers is mathematical literacy.
I would love to hear what others experience is regarding this.
I’ve known a lot of math people, and /on average/ I think they’re more capable of programming useful code than the other college graduate groups I’ve spent a lot of time working with (psychology, economics, physics) /on average/.
That said, the best mathematicians I’ve known were mostly rubbish at real programming, and the best programmers I’ve known have come out of computer engineering or computer science.
If you need a correct, but otherwise useless implementation, a mathematician is a pretty good bet. If you need performance, readability, documentation, I’d look elsewhere most of the time.
Mathematicians are good at writing algorithms, but not at the development aspect, which is basically building for different systems, packaging software and documentation.
I would disagree on the performance part, the vast majority of software developers aren’t writing high performance software and the ones that are tend to be computational mathematicians or physicists.
Just because you’re not writing high performance software doesn’t mean it shouldn’t be a consideration. Sure, I’m not gonna micro-optimize memory when I’m writing an API in Python, but that doesn’t mean I’m not going to write it efficiently.
If I have to store and then do lookups on some structured data I’m gonna use a hash table to store it instead of an array. If I need to contact a DB multiple times I’m only gonna close my connection after the last query. None of this is particularly difficult, but knowing when to use certain DSA principles efficiently falls pretty firmly into the computer science realm.
If you need someone to hyper-optimize some computations then a mathematician might be a better bet, but even those problems are rarely mathematician level difficult. Generally software engineers have taken multivariate calculus/differential equations/linear algebra, so we’re decently well versed in math. Doesn’t mean we don’t hate the one time a year we have to pull out some gradients or matrices though.