It’s hard to conceive the fact that only fifteen years ago there was no term as “data science” at all. Up to date, there’s hardly a single business area that doesn’t need an experienced programming master for diverse coding needs. What has changed, and how simple statistics evolved into such a complex, yet, fascinating discipline? We’re here to reveal it by looking over the timeline of the data science, plus to finally answer the increasingly popular question – what waits for the data scientists in a couple of years from now.

What has laid the foundation for data science as we know it?

Every person who is familiar with data science in its broad meaning knows, that the discipline took a lot of fundamental principles from mathematics, or, being more particular, from estimation theory. It hence was a question of time when the paper calculations were to be replaced with sophisticated computers, which intellectual facilities surpass even the best brains we can train.

However, the belief that computers can perform everything by themselves simply doesn’t stick together with reality! With every year the demand for highly qualified specialists in data science grows exponentially, while more and more companies are ready to hire even the unexperienced beginners that should be tutored by the efforts of the employer themselves. Why so?

In spite of the digital brains calculating abilities, they still lose out to data scientist – even the most unpracticed ones – because the discipline consists of something more than simple data input/output. It is creativity and unconventional approach to the problem that makes so much difference between a person and computer when it comes to machine learning, data engineering, or augmented reality.

Where are we currently? 

For the latest five years, the progress in this area overcame all the groundwork the humanity has collected throughout the centuries. It is now a bad manner to not have at least an inner CRM system developed especially under your company – and we’re not even talking about the gaming industry, where data science entirely marked the new era of entertainment & fun.

More and more businesses find themselves in desperate need for big data department, whether we’re talking about medicine, transportation, software development, or even agriculture. Computational capabilities of the latest computers can be compared to the discovery of a wheel – as cliche as it may sound, the world will never become the previous version of itself. 

But those are some obvious facts. We’re all much more interested in what the future brings, and the predictions are very (very!) optimistic.

What is coming up next?

Statistics that we’ve mentioned a few times before showing an irretrievable growth of both the involvement of big data into our lives and the wage an average specialist in the area gains. Numerous sources compose the tops of professions that soon will field as history – but you certainly won’t find data scientists among those.

It is safe to assume that there are no premises for the trend to go backwards suddenly. And there are even more useful conclusions you can gain from the collected stats.

The demand for specialists is high but will increase even more. With the lack of the solid institutions that educate the future data scientists, there always would be a deficit of personnel; therefore, high salary, comfortable working conditions, and possibilities for self-development in a whole area.

However, the trend has a reverse side. Monitoring the current complexity of the tasks and keeping in mind that it will become even higher, the true specialists in data science have no chance to keep up with time unless they aren’t in step with the progress. 

Data science is a sophisticated discipline that relies completely on the trends in web development. They shapeshift rapidly, which means that even if you are the best developer in a whole world who stepped out of life for, let’s say, a year, you’ll have the equal chances with a complete newbie to catch up. 

“Repeat, learn, discover new” – these are the three pillars of a successful programmer. It is essential to be ahead of time, which you can do either by spending days lurking around the Internet or by using outside assistance, which is available for everyone wishing.

Don’t forget about the titans in data science, that work the way up for the rest world – we are, of course, talking about Harvard and MIT online courses for numerous disciplines like AI, AR/VR, cybersecurity, blockchain, and others. 

And, finally, don’t forget to keep your mind open to everything new, despite how much you wish everything would be simpler as before. 

By following those three ingenuous rules, you’ll surely reserve your place in the sun for the future five, ten, twenty years. It is just like keeping a mind of a child while being an adult: be that get-up-and-go type of person, and we assure you – nothing will be able to threaten your coming career advancement. 

About the author

Sonia Novakivska is a freelance writer working primarily in the niches of AI, ML and Big Data.

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