I wanted to ask about the requirements for Quantitative Finance. I always hear that mathematical ability is all that is required to land and excel at quantitative roles but after talking to some people, they say it is all about coding now. I thought quantitative research roles would still be math-oriented.

I would also like to ask for some recommendations on what should I do as I really feel hopeless right now.

I'm someone who is interested in mathematics and not as much in CS. I'm currently a second-year student doing a five-year dual degree in business and mathematics in Canada (My school is really not that great for mathematics but is the best for business in my country. Yes, I know a business undergrad isn't the place for quant finance but I am stuck here). Now, I love mathematics and I have been self-studying it since last year and most of the topics I know are 1) Topology, 2) Elementary Algebraic Geometry 3) Advanced Linear Algebra, 4) Real Analysis & Measure Theory, 5) Functional Analysis, 6) Some Harmonic Analysis, 7) PDEs and 8) Measure-Theoretic Probability.

Now, I am in a bit of a pickle as to what I should focus my time on. What I had previously planned was to spend my next nine months reading up completely on stochastics and then some numerical analysis. And in my third year, I planned on focusing my time on Statistics and Optimization and getting a feel for ML and even picking up some coding stuff.

1) Is this right? What do you think I should focus more on?

2) Do you think I should even bother with stochastic or should I go all-in on statistics/ML? CS is definitely not my strong suit and I am not that interested in it. I love mathematics and I love finance so I want to do quantitative research.

3) What other careers should I be looking at?

4) Lastly, what are your opinions on not going to grad school? I wouldn't mind going if it is absolutely needed, but I feel like I would be happier skipping grad school.

I would be really grateful if you could help me out.