The year was 2013, and I was fresh out of university. I had graduated as an economics major, and was clueless. Turns out, an economics degree does not make one an economist by career. If only life was that simple. Jobs at bulge bracket banks were fiercely competitive and I was late into the game. The hiring spree was over for research roles at banks, and even then you needed at least a Masters to get your foot in the door.

Overnight, I was a student turned adult out of work, and so the search began for jobs. Entry-level jobs. Everyone's got to start somewhere. And so I landed my first uneventful job but I had seen and experienced how office work would look like. Meetings, conference calls, e-mails. So this was how it is. Also, data! For the former student, the word data just simply meant how much more can I surf the net before I burst my data - mobile data that is.

Perhaps it was the nature of my job(s), or something cosmic which led me in 2015 to another job with crazy big datasets, and I had only basic knowledge of Microsoft Excel to get through it all. It was daunting to say the least. Still, I was up for the challenge. A couple of Google searches here and there led me to Data Science, and Python programming and all its wonders. I needed some guidance in the very information-heavy data science world so I enrolled into a reputable Data Science Programme which ran for 3 months to get my data science journey going. It was one of the best investments I made early in my career to date, not that I am a data scientist by the time I finished the course, but for the fact that it started the ball rolling.

Maybe in the near future, I would go for a postgraduate course in data science just to 'seal the deal' that this is what I will branch into hence forth.

I hope to make something good although small or incremental in the field of economics and data science. If you have or have come across any interesting #econdatsci projects or initiatives, feel free to connect!