Well, I've worked in cryptography orchestration (not actual cryptography, but I needed to understand how it worked from a basic POV) and in reliability engineering which is very stats heavy. Both of those became limited as I got more senior. For instance, a lot of problems can be identified by bucketing them in distributions - I didn't even really know or understand the math for representing a distribution. The long tail of where I actually used that was in a program that I used to create mock data for a set of devices my company was working on that simulated real household resource usage. These same math skills also became problematic as I started to need to learn/understand better applications of algorithms and data structures. There's a lot of assumptions baked in to things like asymptotics that you won't get without a background in math as well. You can certainly memorize certain things, but that has diminishing returns imo. I think I answered the last part above, but I refresh algebra and calculus. I read a stats book, took a Discreet course on Udemy, and read a lot on DS&A. I think that covers it. Took me about 3-4 years to chew through most of what I learned in my spare time.