This topic comes up every so often. I think my previous comment applies here [1]:
I started a Math degree after 16 years of programming without any Math beyond high school (the highest being high school calculus). Most of my work as a software developer didn't require any "higher" Maths.
Once I began studying math, including Modern Algebra, Analysis, Graph Theory, Category Theory, etc., I realized I understood many topics on an informal level, in a non-rigorous sort of way, through programming. I had a good sense of major algorithms and data structures as well as their running times. Once I did have more math under my belt, things did become easier, and I started to see connections and commonality between problems across different domains, i.e. more than one way to skin a cat.
Part of the reason I began studying math, is that I felt it was my limiting factor. The range of problems I could tackle as a programmer was limited by math. It turns out this was partly true.
The biggest misconception is that in Math there is one "correct" answer. This is almost never the case. Some of the most interesting solutions in Computer Science come directly from Math topics that were once considered "abstract". Likewise, some of the most interesting problems are solved through approximation algorithms of seemingly intractable problems, often requiring a bit of "hacking" and real world experience beyond what you'd get from a formal education in Math or Computer Science.
[1] https://news.ycombinator.com/item?id=7104566