Sunday, August 1, 2021

Why the world needs more data science professionals?

As a data science enthusiast, I am quite sure, you are flooded, on a regular basis, with advertisements for data science courses, collaborative diplomas from universities, sales pitches for AI training, and whatnot. Now, you might get an impression that with the spotlight right upon this discipline there must be a terrible rush of people trying to build a career in data science. You might even be discouraged from seeking your place in the likely overcrowded industry. Let me assure you, that this notion could not be further from the truth.

If there is one thing that you will come to learn as you climb up the data science ladder, that is the world needs more data science professionals, right now, than it has. Now, when we say data science professionals, we mean capable and employable resources. The number of enthusiasts pursuing data science training may wildly misrepresent the number of professionals actually making the cut and contributing to the discipline of data science.

What makes data scientists so important?

We keep saying that the world needs more data professionals but hardly ever clarify why. Businesses want to leverage data to improve turnover, reduce risk, enhance cyber security, and optimize customer satisfaction. These are reasons why companies want to hire data science professionals. They need someone to build a strategy and create the data structures and control mechanisms necessary for secure and efficient data usage. The data scientist can create optimal analytical models for the specific needs of a business.

If we look away from the commercial aspect of applied data science for a brief while, it can shape up a whole new perspective for us. Let us just take the time we are going through in consideration. There is a virus outbreak, people have become overly dependent on digital mediums for work. There is an increasing amount of online retail, there are vaccines to be distributed, and healthcare facilities to be monitored. We cannot help but treat the current situation as a tailor-made field of challenges for data science professionals.

Tackling the real-life problems

The panic, misinformation, and emotional breakdown during the initial days of the pandemic had thrown most analytical models off guard. It was difficult to tell the truth from hoaxes, it had become impossible to track behavioral patterns in people. Nevertheless, the relentless efforts of the data analysts and scientists, saw us through. While the pandemic remains as a medical crisis, the data pipelines have taken good shape around the world.

However, there are still problems to be identified and solved. The world as we know it is sustaining a lot of hard blows. The polar ice is melting fast, ocean life is endangered by fishing and oil leakages, child labour is still a problem in many states, people die of hunger every night.

All of these are data science problems. We need more people working on data, looking for patterns, identifying problems, and taking a step to solve them.

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