5 General steps to Ace your next Data Science Interview

Looking to break into Data Science Industry? Any Interview can be daunting, specially one of the highly paid jobs in the market. To set yourself apart from the rest in the list and to show your interviewer that you are the right candidate for the job, include the below 6 steps without fail.

1. Research the role you are applying for

Data Science is a blanket term and there are many roles in this ecosystem such as Data Analyst, Data Engineer, Statistician, Data Architect, Machine Learning Engineer, MLOp’s Engineer and many more. Research the requirement of the specific role and also the business you are applying for in order to avoid fitment issues.

2. Revise your Resume

Customize resume to the Job Description and the company you are applying for. Revise it several times before Interview. Highlight every Data Science skill and mention all the relevant projects with a link(Github). Filter out the things you can do without.

3. Make your Digital presence work for you

When you build a strong, concise online presence like a linkedin profile, it will help you attract employers and land new roles. Online presence is just a way of building your brand and making it public. But make sure to be consistent of posts, videos, or tweets you want to create ahead of time.

4. Practice Case Studies

Data science case studies are tough to crack: they’re open-ended, technical, and specific to the company. Interviewers use them to test your ability to break down complex problems and your use of analytical thinking to address business concerns. Approaching data science cases with a repeatable framework like CAPER (Clarify, Assume, plan, execute and review) will not only add structure to your answer, but also help you manage your time and think clearly under the stress of interview conditions.

5. Go through Data Science Glossary and Terms

Recruiters point-blank like to ask for definitions and what you understand y specific data science terms and concepts. Freshen up on the data Science related terminology terminology by going through relevant glossary and reading up on the concepts.

Last but not the least, Be Confident; You’ve Got This!