6 Steps to Crack Data Science Interview in 2020

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This blog will act as a guide to help you crack a Data Science job interview in 2020. It is an in-demand field and most IT professionals are seeking it. However, to crack this job interview, you must understand a little about Data Science.

Data Science includes concepts like statistics, mathematics, and programming. It also involves Artificial Intelligence and Machine Learning concepts which are yet another significant concept. It consists of several processes like data extraction, data visualization, data manipulation, and data maintenance.

Now, you will read the step-by-step process you need to follow to crack your interview.

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Step-by-step Process to Clear the Data Science Job Interview

Data Science is among the most popular field of study today. Both leading and upcoming organizations are looking for professionals in this field who can help in analyzing and interpreting the data to make informed decisions.

To learn Data Science and become a professional in this trending field, sign up for one of the best Data Science courses.

If you are planning to become a professional in Data Science then, you can keep in mind some of the following tips that will help you in that interview.

Familiarize Yourself with the Various Skills and Roles

The first thing you need to do before applying for a Data Science job is to figure out what are the roles available and which role you wish to pursue. There are numerous roles available in this field including:

  • Data Scientist
  • Data Engineer
  • Statistician
  • Data Visualizer
  • Machine Learning Engineer
  • Data Analyst
  • Software Engineer
  • Data Architect
  • Business Analyst
  • Data Science Manager

These are just a few of the roles available in the field of Data Science. You must spend time in researching about the responsibilities that come along with each of these roles. Further, you must also learn about the skills that you need to acquire for the various Data Science job roles available.

For instance, to become a Data Engineer or a Software Engineer, you should have good skills in programming languages like Python and Java. However, if you wish to become a Business Analyst then you must have good communication, analytical, and problem-solving skills. In this case, it is not mandatory for you to know any programming languages.

After deciding the job role and learning the skills that are required for it, you must get an idea about the type of interviews you may come across based on the role you choose. You need to be familiar with the type of questions the interviewer may ask based on the profile you apply for.

Build Your Digital Profile

All of us are living in the digital era. So, you must make yourself known in the digital platform to crack any job interview, let alone in a technologically advanced profile like Data Science. Most recruiters tend to check your LinkedIn profile before they call you for the interview process.

Before applying for jobs and sending out your resume in various organizations, you need to create a LinkedIn profile. Your profile must be up-to-date as per the job role you apply for and it should be optimized. Updating your profile with the non-technical experience that is generally irrelevant in the Data Science job field might send out the wrong impression.

Also, you must create a GitHub account to keep all your codes and programs in a single place and build your portfolio. By creating and maintaining this profile, recruiters can access and view your work easily. This will give them an overview of your work and they will also be impressed with the documentation you maintain.

The only issue is that you cannot create these accounts just before applying for jobs in organizations. If you create these accounts at the last minute and try to update it, you will not be able to tailor and optimize it as per the role requirements. You need to build these profiles over time with patience and build your network.

Update Your Resume

The most important and also the most difficult step in the preparation process of a Data Science job interview. The criteria on which the recruiters select you varies from one recruiter to another. So, for them to select your resume and give you a chance to attend the interview, you must prepare a concise resume. Following are a few tips that you must follow to build your resume:

  • Ensure that your resume highlights skills that are relevant for the role. Do not include skills that do not relate to your job profile
  • If you are applying for multiple roles then you must tailor separate resumes based on the requirements of the company and the job role

Generally, people send the same resume for different jobs across companies. If you do the same, it is possible that the recruiters may come across irrelevant details and reject you for the same. This is why it is important for you to take your time and prepare your resume based on the jobs and organizations you apply for.

Prepare for Telephonic Interviews

In most organizations, before a face-to-face interview, you will have to go through the telephonic round. In this round, you may have to answer technical questions based on Data Science. These questions are extremely common and basic and you must prepare for them before this interview round.

Try to keep the conversation with the recruiters as formal as possible in a call. Avoid any distractions around you while you are on the call with the recruiter. Further, ask them significant questions related to the company and your job role to show your interest and enthusiasm in the company.

Work on the Assignments

After clearing the telephonic interview round with the recruiter, you might be given an assignment based on your role to complete. You might either be given a problem statement along with the necessary data set to take home and solve in a few days or you might be spending a few hours at the workplace and complete the given work.

Usually, these assignments are given to test your skills and abilities, especially the ones you mention in your resume. The companies may ask you to give a presentation, submit a Jupyter notebook or submit your work on a self-evaluating platform.

Candidates end up making the mistake of covering only the basics of the assignment rather than going further and identifying data patterns. Companies will generate a good impression of you if you make an extra effort in solving the given problem and go beyond their expectations.

Train for Face-to-face Interview

Once you complete all the rounds successfully and developed a good resume, the final round is to attend the face-to-face interview. It is an extremely formal round. Moreover, you might interact with various people during this process including the Data Science team, Project Manager, Hiring Manager, and the HR executive.

During this round, you may be asked to work with the project team and brainstorm on the given issue. The recruiters will then judge you on your thinking abilities, logical and analytical skills, programming skills, your ability to solve problems, Machine Learning techniques, and more. Besides, you might also be required to explain the entire process of your solution or write down SQL queries. So, to crack the Data Science job interview, you must prepare yourself for such situations and also brush up your SQL and analytical skills.

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