To some extent I agree with you, in that all software engineers have to think about refactoring and time complexity, involving a logical or mathematical style of thinking. However, there's definitely a spectrum of how distinctly mathematical the work of a software engineer is.

A lot of front-end development for example does not require familiarity with any algorithms, formulae or mathematical structures. You might need to reason about large systems and have a rough idea of when hashmaps are useful, but the bulk of the work is constructing an interface according to functional business requirements. I frequently see comments here along the lines of "why am I being interviewed about algorithms when I'll never use them in my job".

A more mathematically oriented developer may be in the business of modelling and predictions. They may be confronted with a novel real world problem involving traffic, or trading, or electricity networks, that potentially no one has tried to solve before. They may be required to find a mathematical structure that closely approximates real world behaviour, implement that structure via code, and deploy a continuous model which allows their client to analyse and project.

Of course, you also have academic mathematicians using software like Maple or SageMath to assist with their research. This is another level more mathematical. Perhaps what you're getting at is that people can ask ChatGPT questions like "write me some Sage code to get the Delaunay triangulation of this set of points". I totally agree that it can probably do well at these tasks.

Modelling stuff sounds like data science. It's a term they often use and it sounds very much like the same deliverables you mentioned. I've never seen a data scientist term themselves as more mathematically oriented. Also let's not play around, what you actually meant to say mathematically "superior". That much is clear. Sounds like you know stats and you think that makes you more "mathematical".

You also talk about things like traffic. Modelling traffic is mathematical? Sounds like a simulation to me. Man take a look at GTA. That game is almost entirely made by builder engineers creating simulations. It's the same shit and likely far more advanced then what any data scientist can come up with.

Anyway from your example and from what Ive seen it sounds like you're still doing the same thing. CS algorithms. You're just using algorithms that aren't likely very popular or very specific to data and stats. But adjusting stuff like k-means clustering still sounds like regular cs stuff to me.

There's no point in calling it more "mathematical" because it's not. The builder engineer who wrote all the systems in GTA or even say red dead redemption use a ton of "math" even and they don't term themselves more "mathematical" even though their simulations are likely more complex than anything you will ever build.

That's why when you called your self mathematically superior (again don't deny this.. we all know what you really mean here) I thought you were talking actual math. Because if you looked at a math equation it doesn't look anything like an algorithm. Math equations are written as a single expression. Math equations model the world according to a series of formula. It's very different to a cs algorithm.

Mathematical oriented programming involves largely the same thing and using algebras of mathematics.

If you're not doing this just call it data science instead of trying to call yourself more "mathematical". If you truly were more mathematically oriented you would know what I'm talking about.

Geeze some guy writing "models" and doing some applied math+stats like what every other freaking programmer out there is doing and he calls himself more "mathematically oriented."

Statistics isn't my strongest area. But I do have a doctorate in quantum information theory, so I have some idea of what it means to be mathematical.

Data science definitely forms part of what I do, as my employer stores a lot of data that we use to estimate various parameters. But there's also work on creating bespoke routines for solving vehicle routing problems in niche domains, which I wouldn't really class as data science.

Thanks for the discussion, anyway. I'm not interested in being insulted.

No one is interested in being insulted. But you only feel insulted because what I said is 100 percent true.

"Bespoke routines for vehicular routing problems" lol. I mean phrases like that reveal what you think of yourself as.

You're writing simulations. That's all. "Bespoke" lol. And those simulations have lower fidelity then a video game like GTA which likely does traffic at higher levels of fidelity and real time with a renderer.

I have a doctorate in mathematics. Prior to that I've done work in cs. Doesn't mean shit. I don't name drop that crap to pretend to be superior.