Hey guys, a buddy of mine is in the process of interviews post grad school and will be interviewing at places like DE Shaw, PIMCO, Citadel, MSIM, and so on, all on the quant side of AM (not IT). I gave him some generic advice based on my knowledge of the firms but I wanted to enlist the help of this forum. He has great stats but a completely non-finance background and never worked a finance job. what tips do you have for these interviews?
@DeepLearning" @IlliniProgrammer" @Martinghoul"
thanks!
He will need to prepare for both programming questions as well as mathematics questions. He should have familiarity with a lot of the basic computer science algorithms. They want to make sure that you can write clean efficient code. Nothing too crazy here.
The harder questions are generally the math questions. These can vary a lot more. He should be very solid in upper level undergraduate probability theory (See Sheldon Ross's books on intro to probability and probability models). Many of the questions asked in interviews are based off of exercises from these books. Companies also like to ask lots of combinatorics questions too so he should be prepared for those. Citadel and DE Shaw are pretty purist about evaluating people using straight up tests. Not sure about PIMCO or MSIM but I imagine that those will be a lot more behavioral.
If he's interviewing on the equities side, one big thing is dealing with messy data. Equity data is a pain to deal with. Being able to communicate the process of how you clean up data, do basic sanity checks, etc. is very important. You can have the best model ever but if you aren't able to do basic checks on your data to make sure that it is even sensible then your model is useless. Garbage in, garbage out. Being able to describe this process is important. Although Citadel and DE Shaw have dedicated teams for data cleaning, I still think it's important.
get shit data --> clean data --> try using a model --> model doesn't work --> realize data still shit --> clean data again --> try using a model --> .........
If he's just out of grad school his raw math skills should hopefully be pretty sharp. He should check glassdoor to get some example interview questions. The math questions they ask are generally undergrad level but what makes them tough is you don't quite know what they are going to ask like you do on a college test. He should practice working through problems out loud so that he is communicating his thinking clearly. You can still mess up a question or two and get the job if you demonstrate your problem solving ability through your communication.
TL;DR: Know undergrad probability/statistics questions from Ross' books, be able to communicate how the modeling process works from start to finish (data cleaning, cross validation, variable attribution, parameter tuning, dimensionality reduction, etc.). They won't ask him finance stuff. At most he should just be prepared to answer why he's interested in the firm or quantitative finance in general.
you're a saint. next time I'm in Chicago/NYC/wherever you are, steaks on me (or my buddy if he gets the gig!)
Anytime and absolutely (I'm in nyc)! I wish him the best of luck. The market is very, very hot for quants at the moment so he should be optimistic. Quant firms are pretty desperate for good talent. These firms are even hiring strong fresh undergrads into roles previously only held by PhDs so he should definitely be able to land somewhere.
Another thing that he should consider or at least be aware of is that even fundamental firms are starting to explore quantitative strategies that inform their fundamental process. I've heard of top fundamental/value funds like Baupost group that typically hire ex bankers hiring quants to explore large/unconventional data sets. Although I work at a purely systematic firm, I actually think some of the most interesting quantitative work is being done by fundamental managers ironically. Mining SEC filings and earnings calls, scraping website data from online retailers, etc. is currently being done by fundamental managers. While they don't build systematic strategies using this information, they do use these "quant" techniques to identify opportunities. Unfortunately, many of these unconventional techniques and data sets are only applicable to a handful of companies or industries, which make them irrelevant to a quantitative fund that might have positions on hundreds of stocks. I've also heard that some of these fundamental managers are paying these guys handsomely. To me, it also provides an opportunity to really be innovative rather than make marginal improvements to an existing systematic method through algorithm changes or factor research. If he has an interest, he should def check out those opportunities as well.
Good, meaningful and intellectually-stimulating opportunities are hard to come by, but are out there.
I would love to do something like this.
Any good strategies for quantitative interview prep? (Originally Posted: 03/10/2013)
Going through "heard on the street" to prep for a phone screener at a chi prop shop and an interview at a NY shop, was wondering if anyone has worked through this book, been through through a mathy interview, and had any good strategies for that stuff
Check out glassdoor interviews for Janestreet and the like
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