Data Scientist – a job, a calling, a responsibility to transform our society

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Data Scientist – a job, a calling, a responsibility to transform our society

by Bigdata Doc · March 2, 2017

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As a matter of fact, and by no means intending to sound pretentious, a good data scientist has the choice to pick practically any employer.

Job security is not an issue in this emerging industry. Money matters, of course, but I don’t know many data scientists who choose their employer just based on salary (and those data mercenaries is a complicated species you don’t necessarily want to deal with).

I’ve interviewed many Data Scientists in the course of my professional career. The main drivers I’ve been observing go along the lines of degree of intellectual challenge, creativity space, possibility to make an impact, maturity level of the enablers –e.g.: existing data lake infrastructure, etc-, and some of them –rather data engineers- get quite excited when we mention a particular technology or tool suits.

In this post, I’d like to go beyond these drivers and make an appeal to the data science community. We are in the era of information, where ridiculous amounts of data are flowing from everywhere and every piece of research is turning more and more into a data science project. But we are also in the era of alternative facts, fake news broadcasted at incredible pace by polluted media… where the bias removal has become a really hard task and we are approaching a time where we are literally running out of opportunities to look after our planet.

The time has come for data scientists to realize their potential to make an impact and to develop a sense of responsibility

You got the power

3 decades ago, building a well functioning and production-ready multi-layered Deep Learning algorithm was a mammoth project involving an insane amount of resources and lasting for quite a long time. Massive issues and difficulties popping up from the very first design to the results exploitation in a productive environment and later scaling and maintenance… all along the life-cycle.

Today, with the advent and maturity of Data Science techniques, a single data scientist is in a position of training and optimizing any Neural Network with any of the well-optimized state of the art frameworks (tensorflow, h2o.io, theano, caffe or you name it)… and most probably with a little extra effort, maximizing the computing capabilities of all your hardware components (including your GPU –CUDA-).
Technology and Knowledge empower Data Scientist to drive change. Data Scientist are in control of these techniques and technologies, so their chances of making an impact have been exponentially rising over the last few years.

But more importantly, the awareness of the need for Data Scientist in our Society has enormously changed the perception of the data “worker”: the good old times of “academic” data mining have transformed into modern and sexy “data science” demand from all industries and governments. The lab rat guy who used to run sophisticated models to provide solutions to problems that only exist in the academic world is now a highly demanded data professional with a lot of resources at his disposal having a position in any industry of a his choice… And when he speaks everybody is listening at the recommendations he is able to infer from the data. In some ways, as the industry adopts a data-driven paradigm, this guys is asked to sit in the driver seat… having an indisputable influence in the company steering.

With great powers comes great responsibility

Misusing the data can be very damaging…. We immediately think of hackers, privacy violations, fraud scenarios and all kinds of atrocities… well, of course they can happen, but they are very rare among us data scientists.

But there is much more common way of “misusing” the power… which is the omission of action… Having the tools, having the know-how and the drive and NOT making the most of it to change the status quo is the main reason why transformations happen so rarely.

Maslow’s Hierarchy of Needs’ highest level, self-transcendence –or how to achieve something that’s bigger than yourself- is too often perceived as unreachable in the industry… to certain extent, it certainly is for all types of jobs, but again, data scientists have the choice to get the job where they can have the greatest impact

Your choice

There are companies that are saving lives, curing cancer, combating poverty or protecting our nature and environment. You have the opportunity to make a difference… to make the world a better place… And this opportunity is REAL. Be the data scientist we need, not the one we deserve ?

You can tell your friends that your model predicts the sales by product for a campaign with an error below 2 %… and I think it is amazing…

Or you can tell your friends, that your model improved the yield of a wind power farm by 2%… The first one helps a company to better allocate budget and run more intelligent campaigns… the second one brings us as a society one step further towards 100% renewable energy sources… That’s your choice.

To me, what measures you as a data scientist goes beyond your Kaggle scores, the number of pull requests you got accepted in an Apache project, the number of packages you got to CRAN or the number of downloads of your packages… Outstanding data scientists are those who apply all they can to change our society…

It remains your choice.

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