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For a data science/analyst interview, the interviewer will ask a wide range of topics covering statistics, programming, data modeling, and business prowess.

This guide contains questions broken out by high-level topics that a data scientist or analyst interviewee should expect when interviewing.

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Once you come up with a solution, you’ll probably be asked to explain the run-time of your algorithm and come up with a way to make your algorithm run faster.

You can be a great data scientist or data analyst ever, but if you don’t mesh with the culture that could prevent you from suceeding in the role, or being hired in the first place.

Hiring? We have the data scientist interview questions you need

Statistics and machine learning are important technical skills for data scientists.

They also should be able to articulate what aspects of their technical training have been important in their day-to-day data scientist tasks, and how they can apply their skills to your business.

Data scientists are in short supply, but hiring a good data scientist can help anticipate customer needs, optimize prices, prevent fraud – and more.

We hope these data scientist interview questions can help you find someone with a range of technology skills and a knack for communicating complex subjects to a variety of audiences.

Facebook Data Scientist Interview Questions

The other 2 questions were straight forward group by and join questions .programming question was a bit unexpected for doing in 20 mins.

I guess the interviewer wanted the result in simply a dictionary , but started with what will be the best data structure to store it, to which i answered bi directional graph and then asked me to code the graph, which got me confused b/w the linked list approach and the normal dictionary approach and ended up taking more time.

Recruiter had suggested that phone interview will be around basic data processing question, so wasn't expecting a network graph question at the phone interview level.

109 Commonly Asked Data Science Interview Questions

For a data science interview, an interviewer will ask questions spanning a wide range of topics, requiring strong technical knowledge and communication skills from the part of the interviewee.

From this list of data science interview questions, an interviewee should be able to prepare for the tough questions, learn what answers will positively resonate with an employer, and develop the confidence to ace the interview.

We’ve broken the data science interview questions into six different categories: statistics, programming, modeling, behavior, culture, and problem-solving.

    Table of Contents Statistical computing is the process through which data scientists take raw data and create predictions and models backed by the data.

accordingly it is likely a good interviewer will try to probe your understanding of the subject matter with statistics-oriented data science interview questions.

Be prepared to answer some fundamental statistics questions as part of your data science interview.  Here are examples of rudimentary statistics questions we’ve found: Examples of similar data science interview questions found from Glassdoor:

To test your programming skills, employers will ask two things during their data science interview questions: they’ll ask how you would solve programming problems in theory without writing out the code, and then they will also offer whiteboarding exercises for you to code on the spot.

For the latter types of questions we will cover a few examples below, but if you’re looking for in-depth practice solving coding challenges, visit Interview Cake.

2.1 General 2.2 Big Data 2.3 Python For additional Python questions that focus on looking at specific snippets of code, check out this useful resource created by Toptal.

2.5 SQL Often, SQL questions are case-based, meaning that an employer will task you with solving an SQL problem in order to test your skills from a practical standpoint.

For example, you could be given a table and be asked to extract relevant data, filter and order the data as you see fit, and report your findings.

If you can’t describe the theory and assumptions associated with a model you’ve used, it won’t leave a good impression.  Take a look at the questions below to practice.

There are several categories of behavioral questions you’ll be asked: Before the interview, write down examples of work experience related to these topics to refresh your memory –

Of course, if you can highlight experiences having to do with data science, these questions present a great opportunity to showcase a unique accomplishment as a data scientist that you may not have discussed previously.

and asking questions that clarify points of uncertainty are a great way to show that you know how to ask the right questions (a trait that any data scientist should have).

There is no exact formula for preparing for data science interview questions, but hopefully by reviewing these common interview questions you will be able to walk into your interviews well-practiced and confident.

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3 Types of Data Science Interview Questions

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