Abhishek Ranjan

GL gave me a very concrete framework on how to apply data science to day to day problem statements.

Enroll into a good analytics program

I did my post-graduation in Business Analytics from Great Lakes Institute of Management (GL). GL gave me a very concrete framework on how to apply data science to day to day problem statements. The domain knowledge on business/finance etc proved to help a lot in making sense from the business perspective. GL helped with a lot of job interviews too. The capstone project is a major highlight and gives insights about real life business problems.

Exploit the reach of LinkedIn

Always be active on LinkedIn and connect with relevant people in the market and join data science groups for exposure. I got my job via Linkedin Connection.

Practice makes a man 'data-perfect'

Participate in Kaggle/Analytics Vidhya competitions. Work on a lot of Data Science projects in personal time. Definitely, work on all available Kaggle & Analytics Vidhya datasets.

Ace that interview

Good preparation is key. I was asked to explain LASSO, stepwise regression & other optimization techniques that were definitely difficult to handle. I have changed a lot of jobs, so to explain that was a difficult situation. I also tackled a lot of detailed questions on Data science projects like explaining in detail (on paper) the whole logit model etc.

Make that CV thorough

I was already working with ShieldSquare as a Data Analyst and was experimenting with ML applications for our product back then, this was one of the main causes which attracted a lot of opportunities. Knowledge of Python (Naive though) helped a lot in providing automation plans for analysis. Just Energy had a lot of work on excel, so Knowledge of advanced Excel and Macros helped the most. I was to join the reconciliation department so knowledge in finance was appreciated. But none of this would have mattered, had I missed out any of these on my CV.