Hi Sarah, and welcome to Quantopian!

Just my opinion but I would say a masters in data science (I’m considering this myself) with a focus/courses on econometrics, finance, and accounting would be a great choice.

I have to say, I hold a somewhat contrary opinion. I may of course be downright wrong but in many years of observing markets, little seems to have changed. Least of all their predictability.

If you are looking for great riches they seem to have been achieved by very short term operators who smell out orders and short term direction. Who can quibble with Medallion? However they achieve it.

In terms of longer term investment, I wonder where the real achievements lie? Have lain? Will lie?

Much thunder and many words are spoken, nobel prizes are awarded, but investment remains the simple task it always has been. Diversification.

Do you believe perhaps that the field is bounded? That you can solve it? Perhaps you are right, perhaps not.

Personally and skeptically speaking, methinks your talents would be better spent elsewhere.

Thank you for the responses. I really appreciate it, and value the information.

As for a MS in Data Science: I am hesitant to plan for a MS in Data Science as the field is not concrete, and the degree varies greatly from grad school to grad school. Plus, will Data Science mean as much as Math or Stats in the next few decades? Just thoughts I have gathered through talking with people. I want to also offer information to help others, as I receive help as well.

To address the bounds: I do not have a lot of background with finance and investments, as in none. I have a knack for patterns and numerical evaluations, as well as for picking up math and stats topics. I think that’s a great question, and offers a lot of insight. I will look into this. I have read responses to people on other forums stating one’s talents might be better spent elsewhere than as a quant.

I would love to hear others thoughts and informations. I hope this thread helps more than just myself.

Hi Sarah,

Since Math and Stats are the foundation of data science, the stronger you are in those fields, the easier it will be for you to pick up some of the higher level data science topics. More and more, I think I've developed the opinion that it's best to solidify an understanding in Math/Stats/Programming (this is the best path to become a good data scientist, in my opinion), and then pick another field in which you can apply those skills. My expectation is that having the solid technical background will allow you to explore whichever other field you choose in ways that many others in that field won't be able to. As for what that other field should be, my opinion is that you should pick whatever interests you. If it's quantitative finance that interests you, economics and/or finance programs seem like a good idea, but I'd also suggest exploring other fields. By studying outside of the field, you might find that you can bring a fresh perspective to an industry that is always looking for new ideas! The Quantopian community is certainly filled with a variety of educational backgrounds, and it's really neat to see how it brings out different opinions and perspectives on quant finance topics.

Was looking into this while ago. If you are interested in maths in the field, there's a course in Financial Mathematics that looks interesting to me. Don't have any reference though. Haven't looked at it in much detail as can not be done remote and I'm not in the US.

https://finmath.uchicago.edu/