If you’ve never given an interview before, preparing for your first Data Science interview will be difficult for you if you don’t know exactly what to study for your Data Science interview. So, in this article, I’m going to walk you through the steps to prepare for a Data Science interview.
If you’ve never received a call for your Data Science interview, you first need to know how to present yourself on the Internet to get your first interview. This field has a lot of competition and if you want to get a data science job you need to be different in both your data science skills and the way you present yourself. Here are some of the tips that will help you get your first call for a data science interview.
Steps To Prepare for a Data Science Interview
If you show up for your first data science interview, it will be very difficult if you plan to go over all data science concepts in a limited amount of time. So you need to plan your preparation to pass your first data science interview with confidence. Below are the steps to prepare for a Data Science interview:
- Go through the fundamentals of computer science
- Go through the fundamentals of data science
- Prepare a very impressive resume
- Think about how you are beneficial for that company
So these are the steps that you need to follow to prepare for a Data Science interview. Now let’s go through all these steps one by one.
Fundamentals of Computer Science:
Data science is a combination of computer science and data mining, so since you will be appearing for a data science interview soon, you must have spent a lot of time working on some data science tasks. While working on a data science task, we use a lot of computer science concepts but we don’t notice them.
So the first step will be to focus on the fundamentals of computer science then you have to go through the problems based on data structures and algorithms as you will probably get your first practical question based on Data Structures and algorithms. Here are some of the most popular coding questions based on the concepts of DS and Algo.
Fundamentals of Data Science:
The next step is to go through the fundamentals of data science. Here you need to go through all the concepts where you spend your maximum time working on a data science task so that you can explain what you are doing in your project mentioned in your resume and why you used this approach to solve this problem and not the other approach.
Below are the most important concepts that you cannot skip while preparing for a Data Science interview:
- Data access and collection
- Data preparation and exploration
- Model building and training
- Model evaluation
- Model deployment
- Model monitoring
Prepare an Impressive Resume:
Besides questions based on data science and computer science concepts, the other set of questions is always based on what you write on your resume about yourself. Make sure you don’t write anything wrong on your resume as the interviewer is an experienced person so you can be caught very easily.
So make sure that you can justify anything which is asked by looking at your resume. Try to prepare your resume in a very organized manner. Below is a sample resume of a Data Science fresher.
Think How You Will Be Beneficial:
The most important quality that every business wants to see in you is the way you present yourself. So have confidence in yourself while answering the question of how you will benefit this company.
You’ll get this question for sure, so prepare your answer today by understanding the company you’re going to be appearing for a data science interview. Research about the company and think about how you can contribute to that company with everything you’ve learned so far.
In this article, I introduced you to the most important steps you need to follow while preparing for a Data Science interview. If you have never received an interview call then check out some important tips here that will help you for sure to get your first data science job. I hope you liked this article on steps to prepare for a data science interview. Feel free to ask your valuable questions in the comments section below.