Will Data Science Knowledge Replace Data Scientist Jobs?

By on February 12, 2018
Data Scientist Jobs

We have been hearing for quite a time now as to how artificial intelligence will come to wipe away all the jobs that humans are doing today. It’s a matter of time before you know completely whether it holds any significance or not. But there are other industries too presenting the same dimensions such as data science industry.

Till now data scientists seemed safe from anything related to jeopardy. To say the least, there was a widening gap between supply and data. It was doing rounds as the sexiest job in the world and the jobs are in acute shortage right now. By 2018, scarcity of data scientists will grow from 1,40,000 to 1,90,000.

Excellent data scientist jobs are indispensable to run the data science knowledge industry. But will data science knowledge industry itself sound the demise of jobs in data science? May be. Because we are talking about self-sustaining business analytics which may become independent to operate on themselves.

New NLP technologies and machine learning algorithms banking on advanced capabilities are being leveraged to analyze data, interpret data, and identify patterns- the powers which have the capabilities to replace the data scientists. Google and Microsoft are relentlessly involved in the pursuit of automating the possibilities of what future can hold.

They have gone as far as to say the responsibilities of data scientist jobs can be completed by automation. These tasks are data cleansing, decisions based on optimal features, and development of domain-variations around predictive models. The new generation of machine learning algorithms is used to complete various functions such as reports production which is eventually used for data visualization.

Data Scientist Jobs

It’s foolish to expect companies to not know the informational value and insights from various quarters. If technologies become available at very low prices, then most of the companies will prefer to have such automated and fast-processing platforms in their workplaces. The challenges that they face in doing so, today, without the help of newer avenues, is more about large calculation volumes beyond their capacity to leverage in analytical skills absence.

The technologies in NLP (Natural Language Processing) overcomes such challenges with the help of complex analytics that even people with less technical capabilities can achieve. The huge shortage in the industry of data scientists would be fulfilled by such tools, systems, and platforms working on advanced machine learning and NLP. These platforms are a one-stop solution to allow individuals to work with infographics and various other storytelling devices. Where does that leave people with knowledge in data science?

People today want trained professionals with strong skills in Statistics or Mathematics. Even Gartner says job positions like citizen data scientists will be growing by five times higher than the average jobs in data science, which is the bare minimum. By 2020, companies around the world would allocate 40% budget to predictive prescriptive analysis and business intelligence. As for the careers in the industry of data sciences, they would demand scientists and engineers who are value generators.

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