I have my first ever data science interview soon! What is the best way to prep for it? Do books like Ace the Data Science Interview or Cracking the Data Science Interview help?

Of course it would be sweet to do everything but I just passed the HR screening so should expect an interview in a couple weeks.

Majors: Data Science and Finance YOE: 1

Update: they were looking for someone with A/B testing experience in particular and rejected me. :(

The Data Science Interview book is a completely online and free resource which has been making steady progress over the months.

In the last 1 year it has been used by readers of more than 90 countries. Be sure to check it out.

Recently we have launched a 📖 PDF version of the book at a launch price of $5 🥳, with a commitment that all future releases of the book will be mailed to the purchasers. The proceedings of this will be used to MAINTAIN and keep the online version FREE

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Hi, I'm trying prepare for my DS interviews and I really want to read this book. But it is wayyyyy too expensive for me and really out of my reach to buy it. If someone out there has a PDF version? Could you please share it?

----update-----

I stopped searching for an ebook version of this and felt that this book may have gotten more popular due to hype and marketing. I think if we're to go for any other book out there do the ground work to be a good DS, we can ace it.

There are plenty of other books, GitHub repos too that help.

Good luck!

Hi, can someone please share a pdf version of this book? Ace the Data Science Interview by Nick Singh and Kevin Huo

Hi! One of the mods told me to do an AMA, so here I am for the next 2 days, ready to answer your resume questions, and share some general career & job-hunting tips!

My name's Nick Singh – I've interned at Google as a Data Engineer, and worked at Facebook as a Software Engineer.

During COVID, my career advice on LinkedIn got a ton of traction (now 160,000 followers) which gave me and my buddy (Ex-Facebook Data Scientist turned Wall Street Quant) the idea to write a book to help folks in their data careers.

A year later, Ace the Data Science Interview came out, and it's #1 best-seller and has been read by 30,000 people.

I also run a SQL Interview Platform DataLemur.com with 100k+ users and have a mini-course on Landing a Data Job that's helped a ton of folks too.

I've reviewed a ton of resumes over the years, helped folks with personal branding and LinkedIn networking, and am here to help – AMA!

I have 'Ace the data science interview' bu Huo and Singh. It seems quite good and comprehensive.

I've also had 'Cracking the data science interview' by Lin recommended but have not read it.

Any other opinions?

does anyone have a link for a pdf, epub or even jpgs of the book? I'm outside the US and can't even buy the book because it doesn't ship to my country.

Any help would be great (:

Looking to download the data science interview by kevin hui book. Couldn’t find it anywhere online. Please share if anyone has it downloaded and knows from where it can be downloaded.

Wish everyone a belated Happy New Year, here is what we did in the first month of the year

The Data Science Interview book

• Neural Network section added

• Added new problems in the Probability section

• Added cartoons in a few sections

• Outlier section added

Don't forget to show this project your ❤️ and support

The Data Science Interview book has been making steady progress over the months.

It the last 1 year it has been used by readers of more than 90 countries. Be sure to check it out.

Don't forget to show this project your ❤️ and support

Currently, I am preparing for data science interviews. The "An Introduction to Statistical Learning" and "The Elements of Statistical Learning" are the best resources to prepare for interview questions I know (let me know if you have a better resource/strategy for preparation).

I am wondering which of the two books I should choose for my preparation as the latter goes deeper into the mathematical aspects but at the same time I would prefer the former as there is a Python version and it is easier to read imo.

Which one would you recommend?

I'm not able to find the book for free in the internet, can someone find it plz

Have an interivew coming up where the focus will be on Stats, ML, and Modeling with Python at FAANG. I'm expecting that I need to know Pandas from front to back and basics of Python (Leetcode Easy).

For those that have went through interviews like this, what was the structure and what types of questions do they usually ask in a live coding round for DS? What is the best way to prepare? What are we expected to know besides the fundamentals of Python and Stats?

Out of the blue, I got an interview invitation from Google for a Data Science role. I've seen they've been ramping up hiring but I also got mega lucky, I only have a Master's in Stats from a good public school and 2+ years of work experience. I talked with the recruiter and these are the rounds:

• First Cohort:

  • Statistical knowledge and communications: Basicaly soving academic textbook type problems in probability and stats. Testing your understanding of prob. theory and advanced stats. Basically just solving hard word problems from my understanding

  • Data Analysis and Problem Solving: A round where a vague business case is presented. You have to ask clarifying questions and find a solutions. They want to gague your thought process and how you can approach a problem

• Second cohort (on-site, virtual on-site)

  • Coding

  • Behavioral Interview (Googleiness)

  • Statistical Knowledge and Data Analysis

Has anyone gone through this interview and have tips on how to prepare? Also any resources that are fine-tuned to prepare you for this interview would be appreciated. It doesn't have to be free. I plan on studying about 8 hours a day for the next week to prep for the first and again for the second cohorts.

I want to start giving giving interviews soon for Senior MLE positions (NLP, LLM, Recommendation System etc) Any book recommendations which helps you be prepared well for these positions?

I'm looking for a job again and while I have had quite a bit of hands-on practical work that has a lot of business impacts - revenue generation, cost reductions, increasing productivity etc

But I keep failing at "Tell the assumptions of Linear regression" or "what is the formula for Sensitivity".

While I'm aware of these concepts, and these things are tested out in model development phase, I never thought I had to mug these stuff up.

The interviews are so random - one could be hands on coding (love these), some would be a mix of theory, maths etc, and some might as well be in Greek and Latin..

Please give some advice to 4 YOE DS should be doing. The "syllabus" is entirely too vast.🥲

Edit: Wow, ok i didn't expect this to blow up. I did read through all the comments. This has been definitely enlightening for me.

Yes, i should have prepared better, brushed up on the fundamentals. Guess I'll have to go the notes/flashcards way.

I currently work as a data scientist and have an interview coming up at a company I really want to work at. I made it to the third round, which is basically 3 interviews back to back. 2 of them are technical, one of them is a coding interview. If I nail this, I’m pretty sure I’ll get the job and it would be life changing for me if I get this role. The problem is I’ve been working in a niche area of data science for a few years and I’m not as quick with remembering some of the easy stuff as I did in the past that got me the job I have now. It’s all there though, I just need some feedback to remember what I’m missing, or what I would have said fresh out of school during an interview.

I’m pretty sure they will ask some of these questions for this interview because it seems to be a more traditional DS role than my current one. I just need someone to do a mock interview with. If there is a site that offers these services, I would be willing to pay to use it assuming the price is reasonable. Is there a site any of you have had good experiences with?

Edit: Wow, thank you so much to everyone that pitched in. I really do appreciate that. I’m sure this will be valuable to both me and many others who are in similar situation. Happy studying :D