As the title says, today I will share my own person backstory and how it shaped me for data science to come into my life. As every person on the planet will tell you, their story is a little bit different, and so is mine. Now lets go down memory lane.
From a young age I’ve always been competitive, into strategy games and numbers. If I’m honest it wasn’t always completely healthy, I was always looking to confirm my own uniqueness and intellect when I was very young. For example in primary school from 6th grade you could play chess in a school selection, they would select 5 people and the winner would be table number 1, all the way down to 5 to make a team. We would then as a team of 5 play against all the other schools in the area and number 1 would play against the number 1 of the other schools. I was number 1 3 years in a row, the first time that happened in school history and in my first year I was 9 and playing against these 12 year old’s. I thought it was awesome and it just reaffirmed everything I thought of myself.
Aside from the probably mental health concerns, what I enjoyed so much about chess from an early age is the mix between smart logic and time constraints. At the time I would also play age of empires, a real-time strategy (RTS) game that has the exact same tradeoffs between time and smart logic. This was my next addiction, during high school I competitively played RTS games online, I played a lot of e-sports but this was when the entire esports scene was in its infancy. RTS games taught me 2 things, it taught me how to search for optimal strategies given limited information, and it taught me the concept of studying and improving your strategies outside of the competitive environment, training.
By the time I started my economics studies in 2008 I hit a different period in my life, it was right around when online poker became main stream. This game just perfectly hit my interests, it was a natural evolution after playing RTS games, only the stakes were far more interesting. What was new about Poker? It was more math intensive, it brought me into the world of databases and statistics. It connected to my studies that brought me game theory and behavioral economics.
It was through online poker that I first got into contact with a programming language, there was this professional player who developed his own tool to calculate game theory optimal strategies in a given situation. He did this in python and shared his notebooks with everyone who followed his course. This was a very interesting new challenge for me, by going through his code and altering it to my own needs I self-taught basic Python. Later during my master we did some Stata, which really isn’t programming, but we also had the option to use R. I taught myself R too, just by copying code, looking online and using it for my master thesis.
By the time I finished my studies in Health Economics I was ready for a real job, interestingly enough I was not directly looking for a job in data science, it was economic analysis that was my principal interest. I actually had a job offer in hand from a consultancy in Rotterdam specialist in health economic analysis. At the time of that job offer I just started working part time doing some programming work for a data scientist who worked for this insurance company, MediRisk. He told me that they are looking to expand and got me an interview there. It was my curiosity for something new that brought me to the decision to go with the data science position at MediRisk.
See it can be easy to put something on a page and make it seem like a logical buildup and story, and in a way it was, but the real red line was always my curiosity for something new. Perhaps not completely new, but always one step forward and one step sideways. I love to broaden my view of the world by learning new skills, ideally by doing them. In my job currently I get to constantly explore new tools and technologies, understand them for their potential and excite others to join me in using them to create value. Learning by doing something new is something I aspire to always continue doing.
In a next blog I will share some tips and tricks into what I feel is most important if you want to start as a data scientist.