The Data Daily

Do Data Scientists Still Really Exist?

Last updated: 09-14-2018

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Do Data Scientists Still Really Exist?

It’s a question that’s asked a lot lately, and the truth is, data scientists not only exist — one of them may become president someday. That is a bold statement, to be sure, especially in light of current debate: is the role of data scientist still relevant? One popular notion states that data scientists will soon be obsolete, since automated programs can now perform the analytical functions the role once provided.

But, nothing could be further from the truth.

With the acceleration of technologies and the data generated by them today, the smartest prognosticators believe the role of data scientist will not only continue to exist, but soon morph into an even more significant function within the most savvy of organizations.

The truth is, there is an increasing need for — and a shortage of — good data scientists today. They are almost mythical creatures, in that they must possess a highly unique combination of talents: sophisticated analytics skills, to be sure. Also perfect customer service, spokesperson, strategic and thought leadership skills. Therein lies the challenge: the ability to think analytically and strategically tend to be mutually exclusive. Finding one person capable doing both — and doing both very well — is a modern-day unicorn hunt of significant proportions.

More and more, businesses today are seeking data scientists who possess the training and passion necessary to not only make sense of all of the abundant data, but also glean important insights from it and then, develop an actionable plan based on it. We have yet to develop any automated features or programs that can deliver that kind of strategic thinking.

When you think about it, data science is becoming a part of almost anything we humans do, consume or produce. The recent leak of the Panama Papers exemplifies the importance of data scientists in the daily scheme of things. On April 15 of this year, 11.5 million documents, some dating back to the 1970s, were leaked and unleashed to the realm of public knowledge. The documents detailed financial and attorney–client information concerning more than 214,488 offshore entities. Prior to the advent of the data scientist, even a cross-country team of hundreds of journalists would take years to comb through this magnitude of information in order to unearth any scoops that lie within. Today, data scientists are helping journalists understand the information that’s contained in the documents, and map the relationships between various entities, so they can report on any significant issues and responsibly serve the public’s right to know.

Another similar example involves the auto industry. Up to now, automobile manufacturing has always been about designing and engineering cars that people want to buy. Now, with the development of autonomous cars, data science is playing a big role in determining how well a car will actually drive on the roadways. It will not be surprising when soon, the success of a car company will depend more on the quality of its data science team rather than just its design or engineering acumen.

There are other similar developments in all types of industries and organizations, around the world. Data scientists are — instead of becoming extinct — beginning to drive business and industry strategically. They are becoming more vital to those that provide leadership within our society. So, to extrapolate that thinking, it may not be surprising to see, in 20 years or so, a data scientist as president of the United States.

Granted, data science is still a young and evolving field. As data science and its role in an organization evolves, the data scientist function and their role will also continue to evolve. Data science is still a field viewed by many as one that merely builds models — and building models is indeed a very necessary step in the data science process. But the building of models is just one of many steps required for data science to deliver the impact the discipline is capable of delivering.

Besides modeling, more and more smart businesses will call upon data scientists to first convert the given business problem into a data science problem. Then, an analytical plan must be developed which solves the problem efficiently, identifying and locating data that will be required to run any analytics. Finally, the data scientist will integrate the results of the modeling with the organization’s business systems as a whole.  Throughout all of these steps, the data scientist is key to success. And for the foreseeable future, the data scientist will continue to be key in making multitudes of data relevant to the entirety of the business organization and its goals.

So, do data scientists still really exist? The answer is a resounding yes. For a long time to come, this multi-talented “unicorn” will continue to be sought after, by those businesses truly determined to make the most of this overwhelming — and opportunity-rich — age of Big Data.

Dr. Anil Kaul is the CEO and co-founder of Absolutdata. A prominent and well-known personality in the field of analytics and research, Anil has over 20 years of experience in marketing, strategic consulting, and quantitative modeling. Before starting Absolutdata in 2001, Anil worked at Personify and McKinsey & Company. He has a Ph.D. in quantitative marketing from Cornell University.

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