Ace the Data Science Interview: 201 Real Interview Questions Asked By FAANG, Tech Startups, & Wall Street
Ace the data science interview PDF book is very good, especially for product sense questions. You can't prepare for these questions just by taking classes in your school. But after reading the chapter, I think I learned so much.
Here's my review from the perspective of the candidate. Ace the Data Scientist Interview is proving to be one of the best resources out there for preparing for any type of interview. I've come across it multiple times "in the wild", and recommend it to anyone who wants to prepare for any type of interview! This review is from the perspective of someone who is applying for jobs, so I'll focus mainly on what the book can do for candidates. First off, the book covers the core topics that any data scientist should know, including R, Python, SQL, statistics, machine learning, etc. But it also goes into great detail about things like resume writing, behavioral interviews, and other aspects of the job application process. Overall, I think this book is a must read for anyone who wants to get hired as a data scientist.
I think as a candidate it's good practice to be informed about the topics that will be covered in an assessment before taking it. However, it's also helpful to be aware of the topics that won't be covered. AtDSI is a comprehensive resource covering a very broad range of data science topics. If the authors succeed in their goal of AtDSI being the "Cracking the Code Interview" of data science then you'll also be able to better inform candidates about the topics that won't actually be assessed. For example, if you're assessing algorithms, you might mention that you won't cover recursion or dynamic programming.
Co-author Nick Singh is an experienced growth hacker who knows how to make his ideas work. The book covers many techniques that can help people get into the door and avoid some arbitrary reasons that might cause their applications to get rejected. For the hiring manager, the main benefit is in seeing the examples of interview questions in AtDSi, which are mostly sourced from tech, finance and other major companies hiring data scientists, as they know what kind of preparation candidates are likely to do before coming in. This helps them formulate their assessments. Seeing these typical interview questions will help them understand what candidates are preparing for and whether their assessment questions are typical or not (which could be good or bad based on their goals). You probably don’t want to ask the exact same question that lots of people practice, for one thing!
An absolutely fantastic in-depth tour de force on data science interviews (and more importantly, getting the interviews themselves!). I particularly enjoyed the end-to-end ML interview questions and answers at the end of the book.
Authored by two Ex-Facebook employees, Ace the Data Science Interview is the best way to prepare for Data Science, Data Analyst, and Machine Learning interviews, so that you can land your dream job at FAANG, tech startups, or Wall Street.
Data Science interviews cover Probability, Statistics, Machine Learning, SQL & Database Design, Python Coding Questions, & Product Sense. That's why Ace the Data Science Interview has a chapter dedicated to each topic - it's everything you need for Data Science, Data Analyst, and Machine Learning interviews.
Ace the Data Science Interview has 201 questions from real Data Science interviews, with full solutions for each problem. These interview questions come from companies like Facebook, Google, Amazon, Microsoft, Netflix, Stripe, Uber, Two Sigma and Citadel.
Kevin Huo previously worked as a Data Scientist at a Hedge Fund and at Facebook on Facebook Groups. He holds a degree in Computer Science from the University of Pennsylvania and a degree in business from Wharton. In college he interned on Wall Street, at Facebook, and Bloomberg. Nick Singh started his career on Facebooks' Growth Team, and most recently, worked at SafeGraph, a location analytics startup. He graduated from the University of Virginia with a degree in Systems Engineering, and a minor in CS.
In my book, How to Hire Data Scientists and Machine Learning Developers, I recommend a structured approach to assessing hiring needs and planning your interviewing process. AtHMI in turn provides a structured approach for candidates preparing for interviews. As with my book, I think that it makes sense for hiring managers to understand the other side of the table, i.e. how applicants are preparing for interviews, to help them formulate the most salient assessments of the specific roles they're hiring for. In short: This is a book that your job applicants will read. It makes sense for both parties to get familiar with it.