You may be someone who belong to a field related to mathematics like CS, economics, etc.
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[1] https://math.mit.edu/~dspivak/teaching/sp18/7Sketches.pdf
* Atiyah, Macdonald - Introduction to Commutative Algebra.
* Bourbaki (in French).
* Gasper, Rahman - Basic Hypergeometric Functions.
* Hasti et al - Elements Of Statistical Learning.
* Rudin - Real & Complex Analysis.
* Thomas, Thomas - Elements of Information Theory.
It's hard to find a job that's mathematically more challenging than an academic job. But I believe that there are enough jobs that give you the opportunity to make them mathematically challenging. But you need to take the initiative. Good soft skills and presentation skills help. For example, at my company one of our product lines has over 10 million products per year. These 10 million products can be grouped in 50k "unique" items. It makes no sense that there are so many "unique" items. This is like going to the supermarket for milk and you have to choose between 50k different brands of milk. Without explicit requests from management, I designed a distance metric between these "unique" items (using domain knowledge), which allowed me to apply several manifold learning techniques (in particular, t-SNE and UMAP). (Re)Learning several mathematical techniques along the way. In this way I have an easy to understand 2d picture that can explain in detail which "unique" items are actually unique and which ones are "pretty similar". These "pretty similar" products can be reduced to one unique item. Next to just-doing-my-job tasks, taking these type of mathematical challenging initiatives have always worked out for me and are appreciated by my company.
Summarized, in industry, you should look for a job that gives you the freedom to make it challenging. When you found a challenging task, start applying all the mathematical techniques you know, and try to learn new techniques along the way.
Meier's Groups, Graphs and Trees is much more accessible and visual. Strongly recommended!
Knuth's notes on how to write mathematics well [1] were very influential.
Munkres' Topology is a classic, but I think I leaned more on Hatcher's Algebraic Topology towards the end.
Drobot's Formal Languages and Automata Theory was a lot of fun to self-study.
The Graduate Texts in Mathematics series was always reliable in my experience.
Introduction to Linear Algebra, by Gilbert Strang
A lot of my learning was self study. These books were very helpful to me.
I wouldn't say it taught me the most, but more like it opened the door so I could learn the most out of everything after it.
I am searching for books in mathematics that teach both the how and the why, here: https://news.ycombinator.com/item?id=31650459
I hope to get some insightful answers soon.