Hey, I'm starting a master's program in AI and machine learning this fall (have been receiving letters but not sure where to go yet) with the intention of doing a PhD afterwards. I'm probably going to end up doing research or industry work in my own field as it's my primary plan, but I'm also considering eventually switching to the quant role at some point in my program, as so many people eventually do. It's not my plan, but I'd like to have the option. So what should I do to ensure that it's possible?
A decade ago it looked like anyone who was really sharp and had a hard science PhD could get a great offer on Wall St, but it seems to be more competitive now. There are specific skillsets that you need and you are competing with crack students coming out of MFE programs; I'm not sure exactly what I'll focus on in grad school but Black-Scholes models and trading algorithms aren't it. I'm sure if I research machine learning then I'll be in a good place to work in finance, but I'm not sure about some other areas of AI, like reasoning, knowledge representation, program analysis, evolutionary neural nets, and multiagent systems.
Anyway here are my basic questions about what I will have to do to keep open a good option for quantitative finance work as I focus on AI research in grad school:
1. Is going to a highly-ranked university important? I know that it is extremely important for those who are going to MFE programs, but what about me? And if I have a PhD, would my choice of Master's program matter?
2. Is studying in NYC important? So that you can take internships and meet people while you study?
3. Is it much of a hindrance if I study and research topics in computer science (listed above) that seem to be a bit removed from the skills that quants use?
4. Are quant firms going to know or care much about how impressive my research was in its own field if it's not directly applicable to finance?
Naturally my primary research goals are dominating my decision making but input on this side of the issue would be helpful. Thank you.
A decade ago it looked like anyone who was really sharp and had a hard science PhD could get a great offer on Wall St, but it seems to be more competitive now. There are specific skillsets that you need and you are competing with crack students coming out of MFE programs; I'm not sure exactly what I'll focus on in grad school but Black-Scholes models and trading algorithms aren't it. I'm sure if I research machine learning then I'll be in a good place to work in finance, but I'm not sure about some other areas of AI, like reasoning, knowledge representation, program analysis, evolutionary neural nets, and multiagent systems.
Anyway here are my basic questions about what I will have to do to keep open a good option for quantitative finance work as I focus on AI research in grad school:
1. Is going to a highly-ranked university important? I know that it is extremely important for those who are going to MFE programs, but what about me? And if I have a PhD, would my choice of Master's program matter?
2. Is studying in NYC important? So that you can take internships and meet people while you study?
3. Is it much of a hindrance if I study and research topics in computer science (listed above) that seem to be a bit removed from the skills that quants use?
4. Are quant firms going to know or care much about how impressive my research was in its own field if it's not directly applicable to finance?
Naturally my primary research goals are dominating my decision making but input on this side of the issue would be helpful. Thank you.
