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[D] Quant vs. “Regular” Post-PhD Career Trajectories

Hi all, profuse apologies in advance if this is not the correct place to ask this question. I’ve attempted to look around for information (both online and offline), but perhaps I’m not hitting the right keywords, so I though I’d give this a try.

My question is specifically about “quant researcher” type careers, and what the pros/cons and other considerations are when taking up a job like that.

My understanding is that post-PhD (in ML, or whatever the department is that accommodated your ML research for the bulk of the PhD), the majority of people aim for (1) “research scientist” roles in industry, or (2) focus more on an academic career, or (3) both, simultaneously. Obviously this is a generalization, and there are many more things you can do with any STEM PhD for that matter, but these options seem to be the goals of many people.

What about (4) quant jobs in finance, such as in small/large trading / hedge funds / asset management / etc.? They frequently appear to offer extremely attractive packages, and require no experience in finance. However, for the most part the community seems to be rather separate from the (1) through (3) crowd I mentioned above, so I am unable to get a coherent picture of why some folks choose one path versus another, and the various things you should consider (e.g. long-term career trajectory, exit options, etc.) when taking your first job / internship in finance during / after your PhD.

Apologies for the naive question, and apologies again if this is not the right place to ask this kind of thing. Thank you in advance for your kind advice!

submitted by /u/donb1988
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Toronto AI is a social and collaborative hub to unite AI innovators of Toronto and surrounding areas. We explore AI technologies in digital art and music, healthcare, marketing, fintech, vr, robotics and more. Toronto AI was founded by Dave MacDonald and Patrick O'Mara.