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Here Are Some Tips To Prepare For Your Next Data Science Interview

Here Are Some Tips To Prepare For Your Next Data Science Interview

The Data Science job market is flourishing with thousands of aspirants. To stand out in the crowd and demonstrate your competitive edge is no easy feat.  

But fret not; this article covers 4 important sections of Data Science interview questions: Coding, Product, Machine Learning, Statistics, Modeling, and Behavioural Skills. 

Keep reading for some crucial tips to tackle these questions. 

Coding Questions

What is tested?

Fundamental coding concepts are necessary to simplify complex questions and arrive at solutions. Coding questions put your technical skills to test, and analyze your code quality and thought process while you approach a challenge.

Pro Tips:

  • Practice as many coding questions as possible.
  • Practice understanding the logic behind the problem. 
  • Focus more on real-world data problems.
  • Perfect basic programming concepts and machine learning algorithms.
  • Try to devise multiple solutions to a single problem so that you can compare the strengths and weaknesses of your solutions and pick the best.

Product Questions

What is tested?

Product interview questions make some of the most important questions in Data Science interviews. They test your capacity to understand product requirements, help build products, and navigate through the product’s lifecycle, all while aligning the data strategy with business needs. This is all the more reason to ace product questions.

The following are the three types of product-related questions:

  1. Design a product for the company.
  2. Measure the impact of the product or one of its features.
  3. Scrutinize a metric-related problem.

Pro Tips:

  • Research the product of the organization you are interviewing for.
  • Study the market they play in and understand the competitive landscape.
  • Analyze their customer base.
  • Have a clear understanding of the problem their product is trying to solve.

Machine Learning, Statistics, and Modeling questions

What is tested?

These are non-coding questions that test your expertise in the theory and implementation of these three domains. It has both theoretical and practical questions. By answering them efficiently, you get to prove that you have a foundational understanding of the core concepts that govern Data Science.

Pro Tips:

  • Develop a fundamental understanding of these domains
  • Gain adequate hands-on experience. 
  • Join Data Science Bootcamp to get involved in real-world data science projects.
  • Take up personal projects.
  • Participate in events such as hackathons.

Behavioral Questions

What is tested?

Behavioral questions analyze how you would respond to various workplace challenges and how well you tackle them. You might be asked to describe a previous experience where you resolved a conflict. Your answer will help the recruiter find out whether you are a good fit for the team.

Pro Tips:

  • Make sure you have real stories to share; they demonstrate your skills better. 
  • Start by establishing the context and briefly describe your key responsibilities in the story.
  • Explain the course of action you followed and justify it.
  • Elaborate on the impact of your actions on the conflict.

You can build your credibility by taking up certifications or joining Data Science courses. One of the fastest ways to pick up in-demand skills that are relevant to the industry is through Data Science Bootcamp. They are job-oriented, industry-aligned, and will help you prepare well for your interviews.

Join OdinSchool's 9-month Data Science Bootcamp to kickstart your career in Data Science.

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