Wondering how to crack a Data Science interview in 2019?
INSAID has 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.
Tackling a Data Science interview can be daunting and unless you’re prepared for such interviews and know what to expect, facing interviews and landing Data Science jobs can be a challenging task.
What to Expect from the Post?
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.
We assume that you have applied for Data Science jobs 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 and some common Data Science interview questions but also on conducting yourself during the interview.
Aim for the Top Data Science jobs in 2019!
You are ready with your portfolio and all you need is to learn how to pitch yourself correctly.
Category 1: Pre-interview Preparation
Step 1: Preparing for both General and Specific Data Science Interview Questions
A lot of people don’t actually prepare or think about the questions that they will be asked in a particular interview.
Since at INSAID we prep our students to make them ready for a Data Science Interview, 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 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 specific Data Science interview 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?
- How can you contribute to Data Science jobs?
- 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 Data Science Interview Questions
The second step is to go through all the types of Data Science 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 a Data Science interview.
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 interview 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 Data Science 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, despite 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 taking up Data Science jobs, 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 jobs.
All the best!!
Do let us know about your interview experience. Have a query? Feel free to drop a comment in the comment box below.