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Data Science Interview Preparation With Questions

by YOSS Community Writer, on July 23, 2019 at 10:19 AM

Data scientists are in demand throughout the tech world, but before you can enter the field yourself, you need to ace the interview.

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Just because you are an awesome data scientist, it doesn't necessarily mean your talents will come across in an interview setting. Let’s now go through how you can really shine in a data science interview, from tackling general interview questions to nailing the more specific ones you’re likely to face.

Before The Interview

Almost all companies start with a brief telephone interview where you can put your best foot forward. Just like you’ll do in the actual in-person interview, clearly state why you’re the best candidate and why you’re interested in the role.

Following this, they may set up a formal interview. However, some firms ask candidates to do an assignment where you solve a data science problem. In some cases, an assignment will be part of the formal interview.

Who Will Interview You?

Data science interviews almost always involve many people. They can include:

  • HR
  • Upper management
  • Project managers
  • Team members

The interview may consist of one-on-one meetings, group meetings, or a combination of the two.

Questions from HR and upper management are likely to be non-technical and general. Don't disregard these. Even the most brilliant data scientist won't be hired if the management team doesn't think they will fit in well with the company.

Project managers are likely to ask technical questions and probe you about how you approach problems. Team member questions can be similar. They usually have less experience interviewing, however, so you actually help move the process along by bringing up subjects for discussion. Ask about the workplace culture and how your prospective role fits into it.

Interviewing 101

It's easy to get so focused on the technical side of interviews that you forget about the more basic aspects of interviewing. Remember that under most circumstances, people hire the candidates they like the most.

Here are some things to keep in mind before your interview.

  • Appearance: Even companies with casual dress standards expect interviewees to show up well dressed.
  • Research the Company: Knowing about the company shows interest and allows you to ask informed questions during the interview.
  • Listen and Respond Accurately: You need to actually hear what the interviewers say and respond appropriately.

General Interview Questions

Regardless of how technical a job is, you are certain to get standard interview questions—even from project managers and team members. There's a simple reason for that: they want to know who you are beyond the mechanics of work.

You can find an almost unlimited source of these kinds of questions online. They’re generally easy to answer with some careful thinking. But if they come out of the blue, they can be paralyzing—like the otherwise-innocuous, "Can you tell us a little about yourself?"

Here is a short list of questions that will help you feel more prepared:

  • What is your greatest strength and weakness?
  • What are you looking for in terms of salary?
  • Where do you see yourself in 5 years?
  • Why do you want to work for us?
  • How do you handle stress?
  • What do you do when you disagree with your boss?
  • Why is there this gap in your work history?

Job Search consultant Biron Clark suggests that you work out set talking points:

  • Two reasons you want to work for the company
  • The reason you're looking for a job now
  • A short rundown of your work history
  • Explanations for every career change in your resume.

Technical Data Science Interview Preparation

Technical interviews are designed to test your knowledge. They also provide an opportunity for you to show your communication skills and how you think. With this in mind, be sure to think out loud. Showing that you know how to approach problems is more important than getting to a concrete answer.

Remember that you’re at this part in the interview process because you at least have the basic skills for the job. However, demonstrating that you are a creative and insightful thinker is what is most important.

General Technical Questions

Not all technical questions will be focused on data science. Don't neglect these kinds of questions and queries in your preparation:

  • What development tools do you use?
  • What technical accomplishment are you most proud of?
  • Have you used [product]?
  • Which technical websites to you read?
  • Can you figure out some brain teasers?

Data Science Interview Questions

If you are up for a C++ coding job, for example, the range of questions you will face is pretty narrow. But data science questions can come from almost anywhere.

Below is an assortment of the kinds of questions you are likely to face.

  1. What is selection bias—and bias in general?
  2. What is a normal distribution?
  3. How does the standard deviation differ from the standard error, qualitatively?
  4. What is the difference between interpolation and extrapolation?
  5. Qualitatively, what is multiple linear regression?
  6. What is a Box-Cox transformation used for and how does it work?
  7. Why is cluster analysis used?
  8. What is multivariate analysis?
  9. Write a linked list in pseudo-code.
  10. What are the key features of the Python/R language?
  11. How do Python and R differ in their treatment of strings?
  12. Have you used SAS?
  13. How have you used objects in Python/R?
  14. Which language is better for machine learning: Python or R?
  15. What is deep learning?
  16. What is logistic regression? Give an example.
  17. What is regularization?
  18. What is an example of supervised machine learning?
  19. What is a Support Vector Machine (SVM)?
  20. Provide the breakdown of how you used machine learning in a recent project.

After the Interview

Make sure to follow up with your contact after the interview. This gives you the opportunity to remind them just how awesome you are while also showing your interest in the company and gratitude for the interview.

Summary

Interviews are stressful, but once you have done your preparation, you should remind yourself to stop worrying and try to have a good time. Remember: it's just one interview.

Before the interview, however, make sure to practice, practice, practice. How you do in an interview will have just as much to do with your preparation as it does the actual process.

If you’re looking to make a career move or want to get started in the industry, sign up with YOSS today to get great prospects for data science jobs.

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Topics:Freelancer TipsData Science

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