Mum, I wanna be a data scientist
“You wanna be… what?” - the answer I receive from the 94,42% of humans
Available in Spanish too | Artículo disponible también en español
¿Why a data scientist?
Yeah, at this point everybody knows that data scientist is the sexiest job of 21st century, even on top of influencers, coaches and e-sports players.
I’ve read that so many times I suspect we face a bubble as big as the cryptocurrencies one. Well, I have more indications…
And then… ?
It has also been years since the fields that I have moved in seemed to be reaching the saturation, but at least here in Madrid there is still work for all the programmers, analysts, architects, testers, and all those new words that we have invented.
The decision to choose a specific field should not be in the existing job demand or in the salary (although in this case it seems that both are favorable). The most important thing, as for everything in life, should be personal motivation; and in this case, the goal of trying to be one of those unicorns who like their work :)
A bit of context
Many years ago I finished my studies in Telecommunication Engineering at the Carlos III University of Madrid. A very demanding career if you ask me, and I think that not a grateful one; at least in Spain, the natural way after studying is to be a programmer.
So, you choose a career more interesting a priori than Informatics, to have more fun, and it turns out that you end up doing the same as if you had gone the other way, but with a worse base. Hell! I wanted to play with antennas…
Big data to the rescue
My final project was framed within what we used to call Big Data. The intention was to study a tool called Apache S4, which was used to process data streams in real time, running over Hadoop (by then it was the “rival” of Storm); and also demonstrate its potential by developing an application that used Machine learning. I thought it was great to train a program to learn by itself… maybe I had found the fun I was missing! (although it took me a while to realize that).
A couple of years later, tired of doing exactly the same everyday at work, and maybe driven by the hype that surrounded Big Data at that time, I decided to do a Master’s Degree in <ditto> and Business Analytics, taught by Telefonica engineers specialized in the subject. It was a year without weekends and a lot of evenings/nights in front of the computer, but it was really worthwhile; I could learn a lot of things in a practical way and put myself in the role of data engineers, data architects, data scientists and business analysts.
With the acquired knowledge, I received an opportunity within my company to carry out consultancy proposals for clients, pilot projects or proof of concepts related to data… I had finally arrived where I wanted to be!
Yes, but… no
My work was framed within the Digital Transformation division inside my company, and I didn’t dedicate myself to data related tasks exclusively. In fact, data quickly lost prominence due to the large demand we had in other fields.
In all the time we were trying to get data projects ahead we could see a constant that kept on repeat: the customers wanted to get on the Big Data train, but they didn’t know very well how they were going to make their investment profitable. And even though we told them about the number of applications, use cases and success stories that were going in their sector, it seemed it wasn’t time for them yet: they didn’t have budget or didn’t seem like they were going to get it in the short / medium term.
In addition, although my bosses did trust me, I had the feeling that clients didn’t quite trust the experience we had as a company in this field, because our references weren’t outstanding in Madrid.
In the end, the circumstances led me to another project where I was more profitable, as a micro-services architect. Again separated from the data at work! Although my intention was to continue studying in the evenings, to deepen into everything that would allow me to get the role of data scientist in a hypothetical future project. All right! That’s the attitude! *self-inflicted pats*.
All in
A couple of months ago I decided to ask for a leave without pay, because one of those unpleasant situations in which work and life become a bit incompatible.
The only positive thing about this situation: it helped me to think A LOT. Think about what I want to be when I grow up. Think about what kind of project I want to work in when I return. Think about how I want to spend my free time during this “sabbatical” period. And read. And prepare a plan. And read a lot. And study the viability of my plan.
And suddenly I realized that I’m serious, to such an extent that I have proposed to return as a data scientist (or to die in the attempt xD).
It’s true that my time is limited, and a real ALL IN is not the same as “I will dedicate all the time I have”. But I hope it’ll be enough. The most important thing is motivation, and I think it has been a while since I had so much… I have even started a blog!
Data-driven
I declare myself a fan of data and statistics. ¡Ea!
I’m one of those people still using Last.fm, I even check my statistics almost daily. And for faithful statistics I had to systematically edit the tags for all the mp3s that have passed through my hands. Crazy.
When I was young, I used to enjoy a Spanish football video game where you could choose to simulate the match instead of playing it. And that’s what I did. Always. For me everything was numbers. My decisions were based solely on data.
Related to music I remember that I was in the top 20 in a kind of Fantasy League worldwide organized by Last.fm and Sony; where the scores depended on an algorithm that I tried to understand in order to win (I don’t follow mainstream music!). And related to football I won the Comunio league at work, for 2 years in a row, without being very up to date on the subject. I think that simply I bothered to understand the scoring system… ¡Man Learning!
What better for me than to be able to work with data every day, right? And as my next step I’ll try to use my knowledge to create something that helps society or the environment; you know, the foolish idea of changing the world.
But let’s go step by step… first I have to earn the data scientist label :)
