A great website to practice coding exercises is LeetCode. There are three difficulty levels: easy, medium, and hard. Most of the coding exercises in interviews will be roughly of the level easy and medium. If you are new to coding exercises, we recommend that you start practicing by categories (e.g., array, string, etc.) using the “Tags” feature on the website. Another recourse to learn the basic concepts behind coding interview questions is Cracking the Coding Interview. Because these interviews are technical and statistics students may not have a background in computer science, it is recommended to start preparing the summer before.

StatQuest is a Youtube channel with short videos reviewing basic statistics and machine learning concepts such as logistic regression and neural networks. The videos are of high quality with lots of graphical illustrations. The introductory chapters of Casella & Berger can also be helpful to revisit basic probability. Finally, a short guide to understanding machine learning concepts specifically for interviewing is collected in this ml-interviews repo.

While it is not usually necessary to have a deep background in finance for quantitative finance roles, one type of question in these interviews that are not covered in big tech (MAMAA) interviews is the so-called "quantitative brainteaser" question. These questions aim to test your quantitative abilities which only involves basics of mathematics, probability, statistics, and logic. Two classical reference books are Heard on the Street: Quantitative Questions from Wall Street Job Interviews and A Practical Guide To Quantitative Finance Interviews.