Data Science Interview. Final checklist!

Data Science Interview

Before you go out in the job market and start taking data science interviews. There is some basic ground you must cover, otherwise you will be caught off guard or get rejected for so silly things that you might regret later on!

In this post, through a series of videos, I will give you a perspective of a Data Scientist interviewer like what are the things that I expect from a candidate? What are the common resume mistakes that I see often and wish candidates should have spent some time on them? What are the most important questions which can affect your selection/rejection? How to update the resume? and What are the short-term and long-term study tactics you must follow?

Let’s get started!

How to crack data science interviews?

What are the sure-shot questions which you must prepare? The short-term preparation to cover commonly asked questions and the long-term preparation. What books to read to build a solid foundation in the long run like 6-months/1-year down the line.

Tell me about yourself

This video shows how to answer the first question in your data science interview which is “Tell me about yourself!”. Common mistakes made by candidates and best practices to follow.

If you get this one right! You have just increased your chances of getting selected without even any AI/ML cross-questions! This is based on the psychology of human interaction! Understand this in-depth in the below video.

Tell me about your project

This is the most obvious question which comes after the “Tell me about yourself” or “Walk me through your profile”. This is where the interviewer understands what kind of work you have done so far and the kind of questions to ask you henceforth.

The answer to this question will showcase your maturity. You can distinguish yourself by using a flow that is used by experienced Data Scientists, which I have described in depth in the below video.

Resume mistakes: How many projects should I keep?

This is often a question from a fresher as well a working professional who is currently in some other domain and trying to shift into Data Science.

The confusion begins by not understanding how much time a Data Science project takes for an IT company to finish. As a result, either the candidate puts too many projects for 1-year timeline which is not practically possible, or too few projects.

In the below video I will answer these questions like how many projects you should showcase for 1- year of Data Science experience, you can extrapolate for multiple years of experience using this. How much time a Data Science project takes to finish and what are the steps we take in the industry to complete an AI/ML project.

How to update resume in job portals: common mistakes

Once you have created your resume with all the relevant keywords, the obvious next step is to upload it to the job portals. There are some common mistakes which everyone does and it reduces the number of job calls you get 🙁

There are easy steps that you can follow and maximize your opportunities. I have discussed these in the below video.

What If I am from a non-IT background?

Very common self-doubt is. If you are from a non-IT background like Sales, HR, manufacturing, etc., how can you switch to Data Science?

Even people working in the IT industry have this doubt, like I am from Testing, BI, support, sales background, I have never implemented any ML project so far, how can I show AI/ML expertise/experience?

In this video I have discussed, how can you successfully switch from a non-IT background to Data Science.

How to negotiate Salary for Data Science positions!

One of the most ignored aspects! In fact, it is taboo! We become uncomfortable the moment money is discussed! Be it personal finance or your expected salary. I hope this changes after you read the following lines.

While specifying your expectations in terms of salary (CTC), you often play underdog! You fear that you may come across as a greedy person or a person who is only after money!

Well, please remove these thoughts from your mind, because if there is even a small doubt which remains on your mind that your compensation is less than what you deserve, then you will not give your 100% while working in such an organization. There will always be that voice inside your brain telling you, why work more if the company is not paying me what I deserve? This is very bad for your career as a vicious loop. Because you are not motivated, you will not work extra harder, and if you don’t work extra, if you don’t go the extra mile, you will never grow at the speed at which you should!

Hence make it a point that you should be 100% happy with your CTC compensation before joining an organization.

Think from the organization’s perspective, if you are the HR, and you are getting two candidates with the same profile/experience, one is asking for less salary and one is asking more. Which one will you prefer?

So, if the organization is clear about this to choose the best candidate with the lowest possible salary, then why you should be ashamed of expecting the best possible salary if you have proven yourself to be the best candidate!

Lastly, only you can determine what your 9-hours of daily time are worth? Keeping in mind, this time will never come back! You will not be able to purchase it later on in life! 🙂

There are some “unsaid” rules of CTC that are followed in the IT industry, I will discuss those in the below video, it will help you to arrive at a number for your CTC.

I will also give you tips on how to negotiate with HR, which points are deal-breakers, and what points are good while negotiation.


I hope this post gave you the last pinch of confidence you need to get ready for the interview processes and I wish you all the best for it! 🙂

If you liked this post, then please consider sharing this website with your friends to help them with their interviews and in turn, help me grow as well!

Author Details
Lead Data Scientist
Farukh is an innovator in solving industry problems using Artificial intelligence. His expertise is backed with 10 years of industry experience. Being a senior data scientist he is responsible for designing the AI/ML solution to provide maximum gains for the clients. As a thought leader, his focus is on solving the key business problems of the CPG Industry. He has worked across different domains like Telecom, Insurance, and Logistics. He has worked with global tech leaders including Infosys, IBM, and Persistent systems. His passion to teach inspired him to create this website!

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