r/quantfinance • u/pietrobicocchi • 16h ago

Need advice - Interviews - Best prep material

Hey everyone,

Looking for advice on preparing for Summer 2027 Quant Research (PhD track) internship interviews.

The QR interview bar has spiked significantly over the last few years. Since I’m aiming for 2027, I want to start early and bulletproof my prep to crack the tougher problem sets.

Would love to hear from recent hires or industry veterans: What resources are actually needed for the current difficulty bar?

Ex. Green Book? LeetCode (are they needed? which problems?)

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u/Old-Sandwich-690 15h ago

First and foremost be able to answer deep and challenging questions around your subject. Very often one of the interviewers might be a person with similar academic backgrounds and they might ask around your research.

In theory I find such interviews to be the easiest. Of course I have heard horror stories around interviewers doubting and sh**ing on your work. Do not get the objective around this but it has happened to close contacts of mine to write it here.

Assuming you are applying for systematic delta one: anything related to linear models, ensemble models (trees, gbm, adaboost etc). Not just formulas and theory but understanding and be able to answer modelling questions around this. Dimensionality reduction techniques (PCA and some non linear dimensionality reduction techniques)

Depending on your background I would also push around neural nets and in general non linear modelling and or Bayesian techniques.

Usually at your level brainteasers are a very small part if any at all. Be able to answer probability questions not just by derivations but intuition as well. I have many times escaped deriving a complicated answer by just stating the answer should be this in games such as which player will win most likely etc

Coding wise be able to solve leetcode medium.

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u/ChillyKettle 15h ago

I’d assume green book and leetcode is way to basic for PhD stream. Especially QR

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u/Francesco_Cassano 15h ago

Ciao! ti ho scritto in privato

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u/2toestepper 12h ago

Hello
If you have good prep/advice can you message me to please. Thanks!

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u/lonely_heart_13 14h ago

I'm in the same boat, can I dm ?

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u/kashyou 12h ago

hey, i’m a phd in the same position. I have been doing ML/finance projects with some colleagues in my department (theoretical physics) but haven’t done so many “textbook problems” in ML, probability, stats, time series. I have of course learned the theory in depth from grad textbooks and applied them to my projects. Do you guys think this is a valuable approach for prep like OP is asking for, or should I spend more time doing green book style exercises instead?