You applied for a data science job and received an interview call for the data science job role. Well done! Congratulations!
A Data Scientist Job Interview is not a test of your math and statistics knowledge but your ability to use it at the right time to create business solutions. Studies show that well-prepared candidates fail to clear the tough data science interviews as they are not able to explain their skills in an F2F setting. Even if you are confident about the skills required for the position, have several references at top tech companies and have no impostor syndromes- data science interviews can turn out to be a stressful experience if you are not prepared.
First let us understand the Different Roles, Skills and Interviews in Data Science
The first thing you need to understand is that there are a variety of roles in the data science ecosystem. A typical data science project has a lifecycle that's made up of several functions. A data scientist is just one component in a successful data science project. Here's a quick run through of the different job roles that currently exist:
Make sure your resume reflects the relevant technical skills you'll need for the job. Create different resumes for different roles. Talk to the HR or alumni of the company and see what the expectations are. A startup will usually have very different hands-on expectations as compared to an established corporate firm.
Interview Tip: - Be well prepared with the data science projects you have worked on and ensure that you know each and every minute detail of the project right from how data was collected, prepared and analyzed. If an interviewee is not taking the opportunity to get into the details of the project that they worked on they can never hit the mark in clearing the interview.