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If you are a dedicated Data Scientist, you must be looking for career growth.

Whether you’re looking for external opportunities, higher salaries or growth within an organization, you will face a Data Science interview soon.

Here’s the INSAID Mantra to crack Data Science interviews in 2019. We have put together a 7-Step Guide to cracking a Data Science interview for you. 

This guide has been prepared by our Data Science Expert- Manvender Singh, INSAID Chief Data Science Mentor and ISB and NIT Alumni.

Cracking a Data Science interview can be a daunting task and unless you’re prepared for such interviews and understand what does it take to crack Data Science interviews, facing interviews can be a challenging task. 

What to Expect from the Post?

We assume that you have applied for a particular Data Science role and you have been selected for the interview. The seven steps are divided into two categories:

Category 1: Pre-interview Preparation
Category 2: Conducting Yourself During the Interview

You will get insights on not only how to prepare for the interviews but also on conducting yourself during the interview.

Get your dream Data Science job in 2019. You are ready with your portfolio and you need the right guidance to pitch yourself correctly. At this crucial time, concentrating all your energy on one point is the most sensible thing to do. Start preparing for the interview NOW!!

Category 1: Pre-interview Preparation

Step 1: Bracing up for General and Data Science Specific Questions

A lot of people don’t actually prepare and think about the questions that they will be asked in a particular interview. 

Since at INSAID, we interview our students and make them interview ready, we know for a fact that students don’t even think and prepare well for basic questions like, tell us about your professional journey.

I will advise the aspirants to spend a good amount of time preparing for the general questions that you will be asked. This will not only set the pace of the interview and decide its course but also help you become comfortable.

What you should do next is to prepare for data science specific questions. Here are a couple of them.

  • How much is your experience in Data Science? 
  • Why should we hire you for this Data Science role? 
  • What makes you a good Data Scientist

This will let out a word about your knowledge of Data Science and how confident you are about getting into this field.

Step 2: Study for All Types of Questions 

The second step is to go through all the types of interview questions. 

You don’t need to fret over getting every question right because you can’t get all the questions right; as simple as that. You can’t even go to the extreme level because everything in Data Science is so unfathomable; you don’t know the end to it. 

For instance, if you start going down in a particular algorithm, it will take an eternity and you could have an interview stretching for hours. 

So what you should definitely do is that if you are asked assumptions of a particular machine learning algorithm, of which you are claiming to be an expert, you should know it. This is exactly what is required in Data Science interviews. 

Step 3: Readying Yourself for Atypical Data Science Questions

The next step in this order is getting ready for the questions beyond your regular data science questions. 

For example, you might be asked questions like:

  • Who are the influencers that you follow? 
  • What are some of the blogs that you read? 

If you have answers to these questions the interviewer will get the impression that you know how important it is to stay updated in the Data Science field.

As a matter of fact, you should actually read blogs. Don’t just claim to follow Andrew NG and know nothing about the latest updates he shared. 

You should be prepared for the questions that are not directly related to your prowess in Data Science, but rather your interest in the area.

These were the three steps before the interview begins.

Category 2: During the Interview

Step 4: Be Honest

Be totally truthful and honest in your interviews. A lot of times people seem to claim all kinds of things in the interviews. But an experienced interviewer will clearly make it out whether you are lying or speaking the truth.

For instance, if you have worked on open data-sets and haven’t actually worked as a Data Scientist, do not make tall claims and be honest

Step 5: Stay Calm

Please read that again.

Do not freak out and stay calm.

This is so very important because Data Science, as a field in itself is so vast. You might be asked about just anything in the interview.

For instance, you might be asked about the Support Vector Machine algorithm and you reply in negative. Now you’re mentally freaking out that you’ve been asked a machine learning algorithm and now you don’t know about it.

Take it easy! Nobody is expected to know all the algorithms.

Mold the conversation or the interview in such a way that the interviewer ends up focusing more on what you know, and are evaluating you from that perspective, instead of evaluating you from the perspective of what you don’t know. 

Step 6: Ask Questions

Many times people appear in Data Science interviews and don’t have any questions to ask regarding the roles and responsibilities.

Why is this important?

You might be getting recruited for a Data Scientist role, but Data Scientist in company A is going to be different from Data Scientist in company B. Therefore, you need to know what kind of Data Science work is being actually done.

It lets out a word to the recruiters that you are interested in knowing more about the work they are doing, rather than just desperately hunting for a job and applying left, right and center. 

Step 7: Know What You are Asking For (Salary)

Last but not the least, you should know your salary demands. 

This is indeed essential.

For example, if you are switching from the IT industry to Data Science industry and come up with crazy expectations, without having a lot to substantiate for it, in terms of the work that you have done in Data Science, the interviewers would reject you, in spite of finding you good.  The reason for the rejection will be that your demand for a high salary doesn’t match your experience. 

Know why you are asking a certain salary and whether it is justified or not.

I have seen people entering Data Science roles, who, instead of getting even any hike, have taken salary cuts because they were very clear that they wanted to get into Data Science; you should be open to that approach as well. 

This, I think, is one critical part of closing the deal.

So, this was the step-by-step guide to successfully crack a Data Science interview. Follow these steps and go through them before a Data Science interview and we are confident that you will be on your path to cracking data science roles.

All the best!!

Do let us know about your interview experience. Have any query? Want to clear a doubt that’s troubling you? Feel free to drop a comment in the comment box below. We will love to provide a solution.

Author

Senior Content Writer @INSAID. Data Science and AI enthusiast who loves to read, write and converse.

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