Yeah, most of this thread has kinda garbage responses. Even if you did a CS degree and then did a BMath with a statistics major you still wouldn't have all the

Yeah, most of this thread has kinda garbage responses. Even if you did a CS degree and then did a BMath with a statistics major you still wouldn't have all the skills you would need, though you'd have a great place to start off from. There is an art in kinda guiding / interpreting the mathematics that's hard to teach and most people in the field kinda pick it up through experimentation. I'm sure it will get more formalized at some point, but I don't think the formalization will be all mathematical or scientific; I think much of it will be making explicit how to think about certain domains or a system of process that are useful. Also I think there is a big difference between Data Engineers, Data Analysts, Data Scientists, and AI researchers. Depending on the field, an AI researcher deals more with idealized forms and is much stronger on the mathematics of machine learning. Data engineers are usually stronger on the CS topics that deal with scale. Data analysts, even the very best ones, tend to be weaker on the CS, the math, but tend to be the strongest at quickly understanding data and making it intelligible to decision makers. I'm not knocking it—I was an analyst at one point—it's just the truth that some positions take more skill than others and most great data analysts tend to treat it as a 3 or 5 year stop before levelling up to management or a more technical role. Data Scientists generally have the skills of a data analyst (though they have trouble dumbing things down at times if they came here from something other than an analyst position) with some of the skills from the other two. The way some application code software developers dismiss a whole sub-discipline is kinda embarrassing.