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Talk to data science mentors from Fortune 500 brands

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Learn from industry experts with 12+ years of experience

It’s easier to learn from people who are leading the most challenging data science projects at your dream companies.

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Stay updated about the most recent questions

Learn step by step how to ace the data science and machine learning interview with our full course guide. We provide access to over 500+ recently asked interview questions with 200+ lessons and solutions that teach you the right way to think to pass the interview.

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Solve technical challenges before giving the final interview

30+ take-home challenges from companies like Airbnb, Doordash, Uber, Instacart, and more. We show you exactly what to expect from the take-home challenges and provide solutions with code snippets.

Get hired by world's most renowned brands

Join 1000+ students working at companies like Google, Amazon, Microsoft, Meta, IBM…

Premium members are 50% more likely to land an offer that is 25% higher in compensation at top tech companies.

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Interview Questions

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Data Science Course

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Mock Interviews

500+ real questions, 200+ lessons & 30+ challenges

  • Get access to 500+ real questions asked by recruiters
  • Access +30 take home challenges with solutions and code snippets from companies like Uber, Airbnb, Instacart and more.
  • Ace your data science and machine learning interviews 200+ lessons covering SQL, Python, Product Sense & much more.
Emily Johnson

Emily Johnson


Worked at Google

❝IQ was the most accurate and applicable resource I used to prepare for my Google interview. It made the process easy and allowed me to prepare effectively in a short amount of time.❞
question list

Juan Acosta from Meta increased his salary from $80k to $250k/year and you can too…


I joined IQ a year and a half ago and really loved what it provided. The practices and courses helped my land my Senior DS job. I rejoined again in preparation for my MLE interview, and I found it very helpful for that as well.

It was very easy


Interview Query provided well-structured approach to prepare for Data Science interviews. Practice questions and well conceptualized solutions helped me feel confident and get a job at LinkedIn as a Data Scientist.

Got a support reply within 30 seconds


Learned how to better think through interview problems from multiple vantage points, and improved my ability to write out complex SQL queries. I also found the "Courses" section very helpful.

Saves time & money

Interview strategies shared by our candidates.

personAlex Clough

Worked at Meta

Data Scientist

How did Alex get his dream data science job?

Hello! What’s your background, and how did you get into data science?

Hi, my name is Alex. My background is a Master's in Computational Physics. When I started, data science wasn’t so big yet in 2015, but it started to pick up quickly. I tried to get my foot in data science after I graduated but found out it was really hard. I ended up getting accepted at a bootcamp that helped me understand machine learning fundamentals and algorithms.

I went a really non-traditional route and ended up doing freelance work on Upwork and found a client, Komodo Technologies, that was impressed with some of my initial work. After a few months as a contractor, I got an offer with Statusquota, the CEO's other company she helped work on.

I've heard finding contract jobs on Upwork is difficult. How was your experience?

It definitely started out as doing odd part time jobs. There would be work sporadically for different clients but one day I contacted someone that needed basic modeling work. It ended up being Komodo when they had a posting and needed a contractor, and it made a pretty good way to go into a more consistent gig. I worked as a consultant for about a year until they ran out of resources.

I think trying to gain experience on Upwork is useful since a lot of junior data scientists don’t have experience working with clients and figuring out what a business really wants at the end. When I worked a few jobs in freelance, it gave me the experience of understanding what different businesses needed.

What was your data science interview experience like?

I started getting interviews in Seattle, Florida, and some other places I was targeting to move. I had a strong background in machine learning fundamentals and coding, but had trouble dealing with all the different types of data science interviews. Generally if I didn’t do well, I knew what I messed up on.

Some interviews were somewhat similar like Geico or Statefarm because they were both in the insurance industry. Such as there were problems that were insurance industry specific around solving problems about inequality of where data existed.

Was there an interview that was super challenging?

I would have to say that the NSA position for data science was the most memorable. You get offered to take a data science exam and you end up going into a testing facility where you take an exam at a computer with super tight security, no phones allowed or anything.

Eventually after you leave, you get an email if you passed or not and then they say they'll contact you for an interview for within months. I got the email saying I passed but then I never heard back. The exam was helpful though for showing me what concepts I needed to study for and it filled in a lot of gaps.

The most challenging interview question I had was from an interview with Karat. I ended up making it to the technical interview but then they switched gears and told me that they were looking for more of a data engineer right now instead of a data scientist. This seemed like a pretty common problem, as you can't really do data science until you build out the data infrastructure. The take home assignment was super messy data. It was a lot of exploration in trying to build a good model from messy data.

Did you find any valuable resources for your interviews?

I found Interview Query Premium really useful to me in terms of showing what the questions from other data science tech companies were like. It was really easy to go down the list and ask myself each question and made sure I knew the right answer by checking the solutions as well. I found the situational business questions helpful because the bigger companies like Facebook, Amazon, Google, etc.. are always looking for a specific person with industry knowledge.

I also used a few books. One of them was a practical statistics book by O’reilly which really helped to refresh my memory. A few of the take-homes from companies I applied to and Interview Query had model building where you needed a score at the end to pass. This actually gave me an opportunity to learn more about different boosting algorithms.

What kind of advice would you give a data scientist looking for a job now?

Don’t get bummed. Each company is different and as long as you can takeaway what you learned from the interview, then the next interview will be better. I started looking for a job during covid-19 and was in the final interview process for two companies, and they both had hiring freezes.

My rental lease was ending at the end of April so I was getting nervous that I wouldn't find a place to move to. I began to start my search all over again in Mid-March and tried to change it up to the type of companies I applied to instead of general consulting companies to traditional tech companies.

I found that talking to consulting companies was really strange given the technical screens occurred with consultants instead of data scientists. This resulted in weird case studies.

I ended up finding that the last three companies I interviewed at were my best interviews. They also ended up being the least structured data scientist interviews. But when I had an hour and half conversation with a data scientist which was very casual, I really enjoyed it a lot more since we could discuss the job and responsibilities.

I ended up taking an offer at NetworkNext. The interview consisted of two thirty minute interviews. And they just knew they wanted to give me an offer since they say my enthusiasm for working in the video game industry which has always been my dream job.

What do you think the future of data science interviewing holds?

I think the future of data science interviews need to stray away from take-homes and quizzing people. I don’t think take-homes do anything because they give user practice, but you’re doing a lot of work for not a lot back. When you can just talk to someone about a project, talk about the details, a lot more will reveal themselves.

We cover all data science topics

Everything you need, for any and all data science roles

Product intuition

Understanding how to solve problems before pulling data and how to showcase analytical knowledge to empower business decisions.


These questions test how to write complex implementations of data structures and algorithms for machine learning and engineering focused roles.

SQL & Analysis

Tests data analytics, ability to pull your own data for building models, and different interpretation of datasets and metrics.

Python Scripting

Test basic skills within coding in Python such as text parsing, reading files for writing scriptsor building features out of datasets in Pandas.

Statistics & AB Testing

Needed to understand the basics of statistics, experiment design, and how to effectively measure and implement AB tests.

Machine Learning & System Design

Understanding of how to build, deploy, and test machine learning models in production as well as how to architecting database design for scale.


A focus on testing the interpretation and validation of model building, model case studies, and showcasing an understanding of tradeoffs between technical and business decisions.


Based on understanding the principles behind many algorithms and models.

Our Alumni Got Jobs at These Companies

Data Science Studying Built by Data Scientists


Get coached by experienced data scientists that teach you the intricacies of data science job searching strategies, career advice, interviewing tips and tricks, and how to ace any part of the interview.

Full Course

Learn step by step how to ace the data science and machine learning interview with our full course guide. We provide access to over 500+ recently asked interview questions with 200+ lessons and solutions that teach you the right way to think to pass the interview.


Get access to 30+ take-home challenges from companies like Airbnb, Doordash, Uber, Instacart, and more. We give you an upfront look with what to expect on the take-home challenge and feature example solutions with code snippets.

Frequently asked questions

What does upgrading to premium get me?

The full course gives you the step by step guide and frameworks on how to ace the data science interview. We thoroughly go through multiple data science concepts including product intuition, sql, machine learning, and more. Additionally our question bank provides solutions and mock interviews for over 200+ interview questions and access to over 400+ exclusive interview questions with more added every single week.

You'll also be able to access our SQL, Python and R editors for practice, recently asked interview questions with discussions and company tags, and a community of data scientists to practice peer to peer mock interviews with.

Do you have questions from Facebook / Google / Amazon / Microsoft?

Yes, every single question is curated from an actual data science, machine learning engineering, or data analytics interview from top tech companies. We spend hours crafting each solution to make sure it's easy to understand and conceptualize.

Where do you get your questions from?

We source our questions from various sources, including submissions from real candidates who have attended interviews, as well as scraping from a range of data sources.

Are your questions accurate and recent?

Our questions are all verified by recent interview candidates, to make sure they are real questions being asked in interviews. Questions are sortable by recency date, so you can see which questions are still being asked in recent days.

Should I still sign up if I want a job as a Data Analyst / Business Analyst / Machine Learning Engineer / Data Engineer instead?

Absolutely! All of the various data positions require learning and practicing overlapping concepts and interview questions. For example, some knowledge of SQL and machine learning is generally needed for all data positions. Each job requires a spectrum of knowledge from the more statistical side of product and business analytics to the more engineering side of data engineering and machine learning. Additionally, we work on classifying interview questions asked by different companies and positions on Interview Query. That way if you're preparing for a specific role, you can filter by position titles.

How can I learn more about your coaches and how the coaching program works?

Check out our list of coaches here and more details on how we provide one on one mentorship to help you land your dream job.

How many take-home challenges do you have?

We have over 30+ take-home challenges from tech companies such as Airbnb, Uber, and Lyft with exercises ranging from SQL and analytics to model building.

Do the take-home challenges come with solutions?

About half of the challenges come with example solutions from our network of data scientists. All of them have example datasets to work with.

Can't I get this stuff for free?

you definitely can find a lot of the material online, but most of it is not well organized. Instead our job is to provide a structured way of learning data science and teaching you how to ace interviews with leveled practice. We go through the effort of explaining the solution to the most relevant interview questions, compiling the challenges from recent interviewees, and creating strategy guides to make sure you are expertly prepared for all of your upcoming interviews!

Is it really worth the money?

We think so! $200+ is about two hours of the work day when a data science job salary averages over $130K!

Is there a free trial for the premium subscription?

With the free account, you get a preview to our data science interview course, interview questions, 5 free code editor runs, and three solutions that you can view for free. It’s a great way to test out our platform before committing to it.

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