No matter how hard you have worked on your skills and the number of hours you have put in to learn the subject, it finally boils down to how well you present yourself in the interview. Many applicants crack the aptitude rounds or impress the recruiter just enough to get an interview but are not able to clear the interviews. This article is a step-by-step proven approach on how to crack Data Science Interviews.
1. Take it Seriously
A few candidates do not stress a lot over the interviews since they figure it will get over quickly and will be extremely simple. Some also believe that the telephone interviews are less significant. In any case, it is essential to do your best. Get ready for each meeting, and consistently be proficient. Whether you are giving a Technical Interview or an HR interview, be serious about it and prepare well.
2. Do your research about the company
To get ready for the interview, read thoroughly about the history of the company and its vision. It is highly advised to read the job description again so that you have a clear idea of what the company is expecting. It will help you answer questions regarding how you're the best fit for the work and the organization.
3. Revise what you know
The Interviewer will not ask everything outside of what you already know. Sometimes, we come out of the interview room and then realize that we knew the answer but the thought did not strike the mind during the interview. To avoid such cases, revise the foundation well because even if something has been asked from a different perspective, you are already aware of the concept and can answer it with confidence. The Interviewers will not question you about Rocket Science, even if they do the Data Science concept will remain the same. Hence, revise well!
4. Read something that is trending in Data Science
Being aware of what is happening in the market helps you stand out from the rest. Read a few articles on what are the new algorithms, products, or companies that are shaping the Data Science world. Use this knowledge only if you can relate to what is being asked by the interviewer. Don’t talk about it only to show that you keep up with the news.
5. Body Language and Dress Code
Body language always matters in an interview. A Data Scientist has to communicate his points clearly and be ready to give a presentation to anyone at any point in time. To be presentable, what matters is your dress code and body language. The interview is not the only time when you will be presenting or showing up in front of a senior. Data Scientists often have to talk to clients and seniors and show their work, so the interviewer often imagines you in a scenario when you would be presenting while you are working at their company.
6. Have a good profile on the Internet
The interviewer will ask you about the projects that you have worked on. It is advised to have a good GitHub profile where you post all your work along with a great LinkedIn profile where you regularly post your learnings and build a strong network. Don’t hesitate to talk about your projects no matter how small or big they are because working on projects is the best way to communicate your passion for the subject.
7. Update your CV
Remove everything that is no longer relevant to the role you are applying for and add your latest work and accomplishments. Go through your CV numerous times and remove every line that you are not confident about. For example, let us say you have mentioned 'Critical Thinking' as one of your strengths, now the questions to ask yourself are: When have you used this strength before? Are you confident about it? If yes, let it be in the CV. If you have just copied this from somewhere on the Internet without knowing what it is, remove it immediately.
These are a few ways by which you can crack a Data Science Interview that increases your odds of getting a job in this field. Remember, if you did not make it through an Interview, go home and do your homework on where you think you might have gone wrong. Prepare better the next time you appear for an Interview and ace it!