Quant Researchers: Please Help

MLPhd

Member
Hi,


I was wondering what are my chances of getting interviews from top firms for Quant Research positions (I’m interested in a career change from Software to Quant).

I have PhD+Postdoc in Engineering from Princeton (heavy use of applied ML) and generally a good understanding of probability and stats. I have two YOE at Google in a similar domain and am proficient in C++ and Python. I’m planning to spend 3-6 months for a full preparation.

thanks a lot
 

rajanS

Well-Known Member
Hi,


I was wondering what are my chances of getting interviews from top firms for Quant Research positions (I’m interested in a career change from Software to Quant).

I have PhD+Postdoc in Engineering from Princeton (heavy use of applied ML) and generally a good understanding of probability and stats. I have two YOE at Google in a similar domain and am proficient in C++ and Python. I’m planning to spend 3-6 months for a full preparation.

thanks a lot
You will never know until you apply
 

Onegin

Well-Known Member
C++
Hi,


I was wondering what are my chances of getting interviews from top firms for Quant Research positions (I’m interested in a career change from Software to Quant).

I have PhD+Postdoc in Engineering from Princeton (heavy use of applied ML) and generally a good understanding of probability and stats. I have two YOE at Google in a similar domain and am proficient in C++ and Python. I’m planning to spend 3-6 months for a full preparation.

thanks a lot
Looking good for the home team. Main question - shoot for the stars (DE Shaw, Rentech, Schonfeld, etc?), go big (Two Sigma, Citadel, Millenium), or hit up one of the major asset managers? There's a cottage industry of headhunters prowling the corners of ML / AI / CompSci, Applied Math, etc conferences to snap up PhD talent. Probably you came across these types at some point? Alternatively, Bendheim Center at Princeton could be a good resource for you?
 

MLPhd

Member
Thanks @Onegin and @rajanS for your replies.

My main concerns is that my 2-year SWE experience at Google hurts my changes now -- it may be useful for Quant Developer rules, but I'm more interested in the Quant Researcher roles. I think I have enough educational background (Ph.D. and postdoc in a math-heavy field), however, was thinking if getting a one-year Master of Finance will provide any extra value for my case. What do you think?
 

Onegin

Well-Known Member
C++
Thanks @Onegin and @rajanS for your replies.

My main concerns is that my 2-year SWE experience at Google hurts my changes now -- it may be useful for Quant Developer rules, but I'm more interested in the Quant Researcher roles. I think I have enough educational background (Ph.D. and postdoc in a math-heavy field), however, was thinking if getting a one-year Master of Finance will provide any extra value for my case. What do you think?
PhD is probably a greater demonstration of research capabilities than an MS, especially if you have solid ML exposure. It's not clear MFE will be additive, though you will get a lot of exposure to frameworks and literature. Many of the top MFE's have solid foundations in Stochastic Calculus / Risk Neutral pricing used on the sell side. Some, like CMU, NYU, and Cornell are adding heavy data science / ml components. I think Baruch is as well, though they don't seem to trumpet that as loudly. Princeton seems kind of like a "choose your own adventure" program. Look at Atillio Meucci's "P vs Q" for a high level summary of the differences between buy side and sell side.

Buyside typically has better comp and hours. Sellside is going quant hard, especially w/ automation of fixed income trading.

One mystery for me - the half life of PhD's in the industry seems shorter than in other industries. I can't really figure that one out. Even some the stars in the field seem to have a limited shelf life. Maybe because there is more interaction with internal office politics than in other fields? Could definitely be availability bias on my part.

For continued education, maybe consider Advanced Risk Portfolio Management Bootcamp, or even the "Marathon" more intense program. ARPM Training | Overview . FWIW, I think there is a lot of value in the MFE / MS programs, but most people who go to them won't have PhDs.
 

MLPhd

Member
@Onegin Thanks for the detailed response. Tbh, I don't think I'd need any other degrees to perform well as Quant Researcher. I have taken many courses in probability, stats, and machine learning (regressions, boosting, trees, deep learning) in grad school and recently few online courses on applications of math in finance (martingales, Brownian Motion, Markov Chain, Poisson process, Ito Calculus, Option Pricing). However, I was thinking that If I need to do something else to maximize my chances to get interviews (make my resume shine :D). I feel that without further formal education I'll be able to pass the interviews with 2-3 months of preparation.
 

MLPhd

Member
@Daniel Duffy, I definitely agree, however, do you think top firms give a high weight to PhD in Electrical/Computer Engineering and let me learn finance during the job or solid background in finance is needed?
 

binomial-torrent

Well-Known Member
You could potentially limit your target roles to those that explicitly use ML/AI/the software skills you picked up at google, because there won't be much ML in asset management for example
 

Michsund

Well-Known Member
C++
You could potentially limit your target roles to those that explicitly use ML/AI/the software skills you picked up at google, because there won't be much ML in asset management for example
Probably the best advice here. Many roles are looking for bright PhD’s from top institutions, such as Princeton, and want people with no finance background. So maybe try applying to places that aren’t looking for finance experience. There are many in the industry just look around and you’ll find many. My only advice would be get a resume coach for quant finance who can help maximize your chance of getting interviews.
 

binomial-torrent

Well-Known Member
a lot of the top firms have a specific AI research group, which is a bit different/more niche from the bread and butter QR that you mention in the OP but worth looking into assuming you want to keep doing that kind of stuff

Even some the stars in the field seem to have a limited shelf life.
i would doubt that being well known = star. can you name a single rentech researcher? (besides robert mercer who is er, known for other reasons). on the other hand it’s not clear to me that marco de lopez or what’s that guys name is hitting jackpots (or has ever been)

this is not a field where celebritydom is a currency of any sort.
 
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Onegin

Well-Known Member
C++
a lot of the top firms have a specific AI research group, which is a bit different/more niche from the bread and butter QR that you mention in the OP but worth looking into assuming you want to keep doing that kind of stuff


i would doubt that being well known = star. can you name a single rentech researcher? (besides robert mercer who is er, known for other reasons). on the other hand it’s not clear to me that marco de lopez or what’s that guys name is hitting jackpots (or has ever been)

this is not a field where celebritydom is a currency of any sort.
I agree with you completely- I wasn’t thinking of Rentech, etc but you’re right.

I also agree conference participation / popularity is a poor indicator (maybe even contra) of investing acumen.

I had more sellside in mind; individuals who are legit researchers / practitioners (as opposed to nerd marketers) who made substantial contributions to practice. Its entirely possible many of them made lifestyle choices, so maybe it’s not for me to assume they were pushed out.

thanks for the thoughtful response.
 

MLPhd

Member
You could potentially limit your target roles to those that explicitly use ML/AI/the software skills you picked up at google, because there won't be much ML in asset management for example
Thanks. I'm applying for such roles, in particular, it seems that some firms have "Quantitative ML Researcher" roles at the moment.
 

MLPhd

Member
I plan to apply to Jane Street, 2 Sigma, Citadel, DE Shaw, and Rentech. Do you have any other suggestions? I'm also open to relocate to London or Tokyo for a few years if they have good firms too. Please let me know if you have any other firms in mind that you'd think I should apply for. Thanks a lot.
 

binomial-torrent

Well-Known Member
SIG has an ML team mostly located in the bay area, Voleon is a ML-heavy shop, Hudson River Trading has a deep learning team, you get the point
 

Lynette Zhang

Active Member
a lot of the top firms have a specific AI research group, which is a bit different/more niche from the bread and butter QR that you mention in the OP but worth looking into assuming you want to keep doing that kind of stuff


i would doubt that being well known = star. can you name a single rentech researcher? (besides robert mercer who is er, known for other reasons). on the other hand it’s not clear to me that marco de lopez or what’s that guys name is hitting jackpots (or has ever been)

this is not a field where celebritydom is a currency of any sort.
Maybe quant trading is more competitive than fundamental equity/macro trading. Staying in the frontline for a long time is especially hard.
 
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