Effective long term preparation strategy quant interviews (6 months+)?

doodnewyen · 12/15/22

I'm an incoming QR summer intern at a HF (first experience in quant) and would like to prepare for fulltime recruiting. What do you think is a good long-term strategy for quant interviews preparation (approx 7-8 months)? I think there are 3 main components but I'm very open to other suggestions:

Grind leetcode + probability puzzles. I’ve gotten better at these but probability puzzles can still be hit or miss. I get the fundamental approaches to solving these like looking for symmetry, recursion, drawing Markov chains, coming with simplified examples, etc. Is there a systematic way to train these skills other than just doing more of them and let the intuition build up slowly?
Do a side project. My PhD research is stats heavy but I have decent coding ability. What do you think is a good project that allows me to understand the fundamental aspects of systematic trading + showcase ML knowledge? To working quants, if there is an advanced class in applied maths/stats that you wish you had taken while in school, what would it be?
Networking with people in top firms. Sliding into people’s DMs on linkedin doesn’t seem that effective. My uni’s alumni catalog is not very up to date. I also don’t have a “mentor” in quant finance, like someone I can reach out to ask more specific questions. How do you find these connections?

Background: second-last year PhD in CS/Stats at ~T15 US school.

MMFInfoAcct · 12/15/22

I think you should be giving advice to most of us tbh but I would say just know your research really well and practice discussing it as it would probably be of heavier emphasis during the senior QR interview rounds. From my experience, leetcode + probability puzzles will be asked by the more junior members, the QR leads will usually want you to 'teach' them something or just have really in-depth discussions of certain theories relevant to your past experiences. If you do want to practice, ESL has a really nice chapter of most of the key linear regression ideas for the harder stats questions, and if Green or 150 most frequently asked q's get too easy I'd recommend "Probability and Sto Cal Quant Interview Q's" by Ivan, Rados and Dan. This is in my opinion the hardest quant prep book on the market by far - some of the questions/solutions are overkill but I seen some of the more reasonable ones show up a few times in top HF interviews (I completely skipped the sto-cal sections, sto-cal just isn't all too useful to cracking the buy side interview). The best way to practice for these interviews though is just interview with the lesser known hedge funds since live practice is best practice - no books come close to accumulating actual interview experience. Side projects are mainly just a cherry on top to show your interest in the field - but it's not the main thing. For the networking aspect, just update your linkedin - headhunters/recruitors will naturally find you in your last few years of PhD at a top school. And of course, get the return offer to your upcoming internship - other HFs will almost certainly ask if you got the return offer and why you are choosing to recruit even with a return offer (so have an answer prepared for that)

AppliedMath · 12/19/22

1. Probability puzzles are a good idea. As for the other things on leetcode, forget grinding. You might as well memorize them... assuming you are not trying to be a Quant Dev.

2. Do this first. Suggestion: use encoder-decoder for an aspect of pricing, such as substituting it for a parametric interest rate model. As a PhD student you'd be able to code this into something presentable fpr github (don't skip making a useful readme.md). You could additionally turn it into a short (less than 10pg) paper, which can be divided into chapters and added to your Linkedin profile, or posted as a story on LinkedIn over a a few weeks. Start turning anything you've coded thus far into a Github gist or file within a repo on Github. Comment your code.

3. There are ways to ask questions on LinkedIn that lead to fruitful conversations. However, enabling the "I'm looking" badge (visible to recruiters only mode) would probably yield results at the same rate.

Have someone review the layout and presentation of your CV.

I'm assuming this is 6+ months because you've yet to graduate. Otherwise, this is a 2-3 month process. Some people would even apply to a few places now, and know what to expect in order to narrow down their prep tasks. However, you'd have to be okay doing so even though you don't intend to work there while finishing your PhD.

doodnewyen · 12/19/22

MMFInfoAcct said:
I think you should be giving advice to most of us tbh but I would say just know your research really well and practice discussing it as it would probably be of heavier emphasis during the senior QR interview rounds. From my experience, leetcode + probability puzzles will be asked by the more junior members, the QR leads will usually want you to 'teach' them something or just have really in-depth discussions of certain theories relevant to your past experiences. If you do want to practice, ESL has a really nice chapter of most of the key linear regression ideas for the harder stats questions, and if Green or 150 most frequently asked q's get too easy I'd recommend "Probability and Sto Cal Quant Interview Q's" by Ivan, Rados and Dan. This is in my opinion the hardest quant prep book on the market by far - some of the questions/solutions are overkill but I seen some of the more reasonable ones show up a few times in top HF interviews (I completely skipped the sto-cal sections, sto-cal just isn't all too useful to cracking the buy side interview). The best way to practice for these interviews though is just interview with the lesser known hedge funds since live practice is best practice - no books come close to accumulating actual interview experience. Side projects are mainly just a cherry on top to show your interest in the field - but it's not the main thing. For the networking aspect, just update your linkedin - headhunters/recruitors will naturally find you in your last few years of PhD at a top school. And of course, get the return offer to your upcoming internship - other HFs will almost certainly ask if you got the return offer and why you are choosing to recruit even with a return offer (so have an answer prepared for that)

Thanks, I checked out the prob and sto cal quant interview book you mentioned. Definitely a lot of hard questions (some look like they're impossible to solve in a 1 hr interview lol). On your point about sto-cal, do you happen to know how things like stochastic ODEs, PDEs are used in buy side firms? Sell side desk quants at BB do seem to use them a lot but I can't find much about their use in buy side on the internet.

doodnewyen · 12/19/22

AppliedMath said:
I'm assuming this is 6+ months because you've yet to graduate. Otherwise, this is a 2-3 month process. Some people would even apply to a few places now, and know what to expect in order to narrow down their prep tasks. However, you'd have to be okay doing so even though you don't intend to work there while finishing your PhD.

Thanks a lot for the suggestions! I applied quite broadly this past internship recruiting cycle and interviewed at some of the big names like Cit, HRT but wasn't good enough/didn't prep enough to make the cut. I think I have a decent idea of what to expect now (assuming new grad recruiting ~ internship). I like to plan ahead so I can perform better next year.

I'm worried that if I apply for new grad now, I'll be interviewing in Jan/Feb if selected. Then when it's actual new grad recruiting season (Aug-Sept), wouldn't that be too close and some firms will blacklist me?

Andy Nguyen · 12/19/22

Take a look at the interview books in my Master Reading List (in my signature)

Master reading list for Quants, MFE (Financial Engineering) students

QuantNet International Guide to Financial Engineering Programs DOWNLOAD GUIDE FREE QUANT CAREER GUIDES What do quant do ? A guide by Mark Joshi. (see attachment) Paul & Dominic's Guide to Quant Careers (see attachment) Paul & Dominic's Guide to Getting a Quant Job (see attachment) Career in...

quantnet.com

Phi-quant · 4/17/23

MMFInfoAcct said:
I think you should be giving advice to most of us tbh but I would say just know your research really well and practice discussing it as it would probably be of heavier emphasis during the senior QR interview rounds. From my experience, leetcode + probability puzzles will be asked by the more junior members, the QR leads will usually want you to 'teach' them something or just have really in-depth discussions of certain theories relevant to your past experiences. If you do want to practice, ESL has a really nice chapter of most of the key linear regression ideas for the harder stats questions, and if Green or 150 most frequently asked q's get too easy I'd recommend "Probability and Sto Cal Quant Interview Q's" by Ivan, Rados and Dan. This is in my opinion the hardest quant prep book on the market by far - some of the questions/solutions are overkill but I seen some of the more reasonable ones show up a few times in top HF interviews (I completely skipped the sto-cal sections, sto-cal just isn't all too useful to cracking the buy side interview). The best way to practice for these interviews though is just interview with the lesser known hedge funds since live practice is best practice - no books come close to accumulating actual interview experience. Side projects are mainly just a cherry on top to show your interest in the field - but it's not the main thing. For the networking aspect, just update your linkedin - headhunters/recruitors will naturally find you in your last few years of PhD at a top school. And of course, get the return offer to your upcoming internship - other HFs will almost certainly ask if you got the return offer and why you are choosing to recruit even with a return offer (so have an answer prepared for that)

Thank you! That's helpful. What are ways to find those lesser know hedge funds for someone who doesn't know the names that much? I only see a list that's from 2016.