EP8 – Data Scientist | The Why & The How

Hello People,

After some time on this blog and reading reviews and related documents. I think it seems legit to assess what I have been up to and if my thought as a Data Scientist are getting clearer. Let us get back to the why and the how of this great adventure…

In early February; I explained my choice of heading to be a Data Scientist via this short paragraph :

In fact; I was googling and reading reviews (as usual) and found the Data Scientist thing on HBR being rated as the Sexiest job of 2016. Damn ! For the first time brainy job was considered SEXY AS F**K. So I took the decision of getting into this great adventure over the 5 following years and become a PhD Data Scientist in 2021.

Meanwhile; I described the Data Scientist as :

According to various articles and videos I have the chance to read and see, a major tendency emanated: “The Data Scientist can be of multiple nature; the latter can either be the an Excel Sheets Master and making figures speak, or  a Data Visualization Artist, or a Virtuoso of Statistics, or an ERP/CRM Expert, or a  MySQL Practitioner, or a  Data Mining Ninja, or even better ALL OF THE ABOVE.”

Let us say it summed it all due to my initial point of view. But with some review of my statements I should enhance those.

Data Science for Dummies

Basically, Wikipedia explain Data Science as the following : Data science, also known as data-driven science, is an interdisciplinary field about scientific methods, processes and systems to extract knowledge or insights from data in various forms, either structured or unstructured, similar to Knowledge Discovery in Databases (KDD). On the other hand, Datajobs gives the following description : Data science is a multidisciplinary blend of data inference, algorithm development, and technology in order to solve analytically complex problems. However; a comment on Quora simply said that : Data Science is the practice of Asking questions.

Recently, I read a book: Freakonomics, written by Levitt & Dubner. This got me thinking a lot and while turning pages and getting insights I came to the conclusion that :

Economics questions do not only turn around capital markets, inflation or related analysis. In fact, it was simply the study of how someone goes to his aimed target via available resources. This hit me ! Damn; it was this simple and it had an impact on my views of becoming a Data Scientist. Indeed; it did not shattered my dream; but it allowed me to narrow the path to get there.

I want to become a Data Scientist; who will get  a bunch of data but will have as scope of work the analysis of arising life matter and getting insights for sharing.

I don’t want to be the kind of guy needing to get through massive speculation and getting my science so complicated that I will be the only one to understand my shit. With the booming of internet; the gap between the expert and the amateur; is no more the knowledge; but the way this knowledge is used. I will then focus on building up methodology and getting Data Science done my own way by following Levitt, Dubner and Quora statements : Ask Questions.

How to do so?

For the upcoming weeks I will be getting on the work of fellow Data Scientist around the world. I will write an article about each of them and will thus state if the later is a role model I wish to follow. By end of year I think I will be able to generate my THEME.

By dropping simply those keywords “Data Scientist Listing” in Google, you come across a freaky list. Lot of names, with one common trait; Data. So let get the ball rolling and get this section about Data Scientist filled up. It is time to get the path cleared.

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