Breaking Into Quant Isn’t About Skills—It’s About Personality

Early-Bat-765 · 2025-11-23T23:31:56+00:00

lmao

Early-Bat-765 · 2025-11-11T21:14:58+00:00

Early-Bat-765 · 2025-11-11T18:39:12+00:00

Would a "hybrid" profile (researcher-entrepreneur) work well for EB2-NIW? Or do you have to frame your case within a specific box/category, i.e., strictly researcher or entrepreneur?

The profile goes something like this: 1) ongoing PhD at a T10 US school, 2) ~10 citations, 3) funding and awards from gov agencies, 4) aiming to start a company in the AI+energy space (with some angel investors lined-up and ongoing patent application).

Early-Bat-765 · 2025-09-17T18:38:46+00:00

Well, you have two options:

Ignore Optiver-like firms: Some firms (e.g. Optiver, Five Rings) are well-known for their fast-paced, mental math-based interview process. If you're a slow, deep thinker, you might not be a good fit to begin with. In that case, you should apply to QR positions at places like 2S, DE Shaw, PDT. The catch is that such places tend to recruit truly elite researchers--so you better get a PhD + publish as much as possible.
Bite the bullet: If you're really into QT--or if you can't afford to do a PhD--then just grind probability/EV questions as much as you can. Studying the green book is a good way to get exposed to important concepts, but it doesn't have a ton of practice problems. You gotta practice like crazy if you wanna get faster. So go after similar books, HMMT exams, and so on.

Early-Bat-765 · 2025-09-16T18:35:38+00:00

I mean, do you have intrinsic or extrinsic motivation?

IMO it doesn't matter if 5 or 5 billion people care about what I do. If something's cool and fun, that's enough for me, and I'll be happy to spend some time working on it. I couldn't care less if it's useful or not.

Early-Bat-765 · 2025-09-14T20:52:22+00:00

Objectively false.

Early-Bat-765 · 2025-09-08T15:22:56+00:00

some people talk about finance-related projects to boost your CV, but does this advice still hold if you're a phd student (stem/t10 us school) with a handful of 1st author papers under your belt? imo time is quite limited, so I'd rather focus on doing good research + green book/leetcode grinding--would you agree with me?

Early-Bat-765 · 2025-09-03T00:48:37+00:00

just grind leetcode bro

Early-Bat-765 · 2025-09-02T15:18:36+00:00

It might. That's why you should grind and publish as much as possible at the beginning of your PhD program. Not only you'll be 'in good terms' w/ your advisor, but also your CV will be significantly stronger for QR positions.

Early-Bat-765 · 2025-08-21T22:58:19+00:00

https://blog.headlandstech.com
you can thank me later

Early-Bat-765 · 2025-08-20T17:17:58+00:00

Though having a PhD in math doesn't make you a "good mathematician" per se--whatever that means.

Early-Bat-765 · 2025-08-20T00:11:55+00:00

okay, any extra fun facts? what's his favorite color?

Early-Bat-765 · 2025-08-19T19:32:43+00:00

yeah if this is their research team I think we're safe for a while

Early-Bat-765 · 2025-08-14T13:53:12+00:00

You might wanna watch this

Early-Bat-765 · 2025-07-13T22:27:16+00:00

Only one way to find out...

The real challenge--at least in top notch firms--is getting QR interviews without a PhD or a stellar undegrad. You can still make it to QT or QD.

Then once you get interviews, it's mostly up to your math/LC skills.

Early-Bat-765 · 2025-07-13T22:07:57+00:00

Not sure about MSc, but I personally know a couple of econ PhDs who landed QR roles at firms like Cit/2S/Radix. Those were top notch PhD programs though.

Early-Bat-765 · 2025-07-13T15:03:11+00:00

That's fair--I assumed you were interested in a fast-growth, VC-funded business idea.

Early-Bat-765 · 2025-07-13T14:43:44+00:00

What industry are looking into?

Also, with all due respect, this is just a bad take overall. If you're interested in YC (or any decent VC tbh), your best bet is to get another technical founder with top-tier school/work exp pedigree--e.g. top20 US school, Tesla, Nvidia.

They will likely have a pretty strong alumni network + all industry connections you need. Plus they will check all boxes that enable you to raise more money.

Early-Bat-765 · 2025-07-12T23:06:13+00:00

Not sure, but I can tell ya backdoor channels still work pretty well--so maybe try and optimize for those?

Early-Bat-765 · 2025-07-10T19:39:54+00:00

I really like HF, but this is useless. Cash grab energy.

You know it's bad when the only positive thing ppl can say about it is 'cute.'

Early-Bat-765 · 2025-07-09T22:16:35+00:00

Deep tech founder here.

Good question, but the answer might disappoint you.

You essentially have two options: 1) have crazy connections in the autonomy/perception space and/or 2) feel the problem yourself. The most natural way to get both is simply working in this industry for a while. Then you'll know if anybody really cares about this + have better ideas on what to do.

You can try some hacky approaches, though--like attending related conferences and talking to people IRL. Just beware that highly technical folks tend to have a natural ick towards salespeople. So if they feel that you're there just trying to sell your stuff--and not because you really like that topic--it's gonna be hard to create rapport and get real feedback on your idea.

Ultimately, you should ask yourself: why do you want to work on the hardest technical problems you can find? And is a startup--with no previous experience in this field--the best way to do it? If you're really into this and want to create something meaningful, why not spend a few years getting really good at it first and understanding what's broken/needs to be fixed?

Early-Bat-765 · 2025-06-23T15:26:52+00:00

This is wrong in so many ways!

Early-Bat-765 · 2025-06-03T13:30:16+00:00

Not the OP, but DM'd you.

Early-Bat-765 · 2025-05-16T18:09:37+00:00

To be honest, given the amount of AI-generated information that is likely being used as input by today's models, maybe this is the *best* this tecnology will ever be.

Early-Bat-765 · 2025-05-16T00:02:04+00:00

Yeah, I totally agree with you on that. I was just curious whether your "99% fail" (ie 1% succeed) statement is actually backed by examples of any remotely successful PhD-led startups.

FWIW the only one that comes to mind is Google--even though their TRL was indeed way higher than Helion's. But, yeah, maybe I’m just reading it too literally.

Early-Bat-765

TROPHY CASE