Welcome to Interview Query!

We've curated hundreds of Data Science interview questions across 100+ top-tier tech companies, sourced by community members who've recently interviewed at these places.

Prepare for your upcoming interviews the right way by answering these interview questions and learning from Interview Query's community of experienced data scientist.

Onboarding

If you are a new user, please follow these three simple steps to get started:

1. Use your existing IQ account to access the questions. Login here!

   • Please note that for now, full access is granted only to users who have purchased one of our subscription plans. For more info about our plans, check out our pricing page!

   ---

2. Use our filters to find specific questions based on specific types of questions you want to practice with, your role, difficulty, and the company you're targeting. Our filters also allow you to find questions you've saved or completed.

   

   We also support sorting so you can find questions based on rating and recency!

   • "Sort By: Top Rated" lists questions in descending order of upvotes. The top of this list are questions that have the most upvotes.
   • "Sort By: Recently Asked" lists questions in descending order of recency. The top of this list are the questions asked by companies most recently.

   ---

3. We recommend you first try answering the question without looking at other answers. This way, you'll be able to come up with an original answer, maximizing the efficacy of these practices.

   

   ---

   • If you're ever stuck on a problem, click the "I need help" button. This will bring up a list of "hints" that will help guide you towards a solution.

   

   ---

   • When you think you have a solution, click the "I've got an answer" button. This will bring up a list of "gotchas" to check your solution's logic. After going through the "gotchas" you can view a solution by clicking "show solution"

   

   ---

Using Code Editors

On Interview Query, you can use our online SQL and Python editor to solve questions; we currently support MySQL 8.0.17 and Python 3.7.

Use the SQL editor to write SQL statements and run queries.

Use the Python editor to create functions and write test cases to build an optimal solution.

Community Guidelines

1. After coming up with a solution, check out the "Details" tab and upvote the question if you found it helpful. Also, if you want to leave any feedback for the question click on the "Give Feedback" button at the bottom of the section.

   

   ---

2. Next, check out the "Comments" tab and browse through others' answers to learn from the similarities and differences in each approach. Feel free to share your solution, leave feedback, and discuss with other community members. Upvote answers that you found particularly insightful or downvote any that you think needs review.

   

   ---

3. Build a habit of practice to improve your interview skills effectively. The key to improving is consistency. We recommend you designate 30 minutes every day to practice. Answer questions, share feedback and learn from Interview Query's community of data scientists.

   • Strive for complete, quality answers, as if you were in an interview setting. The more similar you make your practice to the actual interviews, the faster you'll improve.
   • Imagine the readers of your answer as the interviewer. Provide a clear framework of your answer, a structure behind your thought process, and the heuristics behind your decisions to make sure the readers follow your answer. It will also help you get more clarity in your thinking.
   • Embrace feedback from others as it's the best way to get better!
   • Be respectful to each other in providing and receiving feedback. Provide constructive feedback and have empathy for every member of the community. Please note that we may remove offensive answers and comments.