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Data scientists: The new ‘sexy’ job in 2016

Data scientists: The new ‘sexy’ job in 2016

The skills required for data scientists in the big data domain are not explicitly taught in graduate college, which puts a lot of burden on organizations to train existing as well as the new workforce.

By Noah DMello
Feature Jan 27th 2016

With an emerging technology like big data making it big, there will be a shortage of talent to take advantage of big data, simply because institutes have not churned out the right kind of talent. But not many institutes, especially in India, are stepping up their game.

By 2018, in the US alone there could be a shortage of 140,000 to 190,000 skilled data analytical workers as well as 1.5 million managers and analysts who could use big data analytics to make effective decisions.

For the long run, analytics organizations are now looking at hiring recent graduates who have solid quantitative prerequisites.

Once integrated in the system, data scientists do not have it easy. “In a day, 80 percent of the time data scientists spend in pulling data together, cleaning it and making sure that it is in the right format, while they spend 20 percent of their time in analyzing the data,” said Charles Race, EVP, Worldwide Field Operations, Informatica.

Samiron Ghoshal, Partner & Leader-IT Advisory Services, EY

However, Samiron Ghoshal, Partner & Leader-IT Advisory Services at EY, has a different outlook toward this.

He feels that data scientists come only in the “churning” part of the process. In addition to domain knowledge, there is a need for people who also understand the business aspect.

“Right now I’m seeing organizations hiring not only data scientists but also lawyers, doctors, business leaders, and others to analyze their business needs,” he added.

However, can one rely completely on automation or some level of human intervention is necessary while making analytics-based decision?

“The need for near-real-time business intelligence based on stream processing is growing quickly in almost every industry. Stream processing has already transformed financial markets—the majority of equity trades are now conducted algorithmically in milliseconds, offloading work from traders and changing the costs and benefits of trading strategies... The fastest growth in stream processing usage in the next five years will likely be in the Internet of Things, which generates streams of sensor data,” said Bhavish Sood, Research Director, Gartner.

But what should organizations do to get the best analysts on board?

Sood said that training existing statisticians, scheduling projects on analytics marketplaces like Kaggle, and working with universities and academics as advisors on the organization’s initiatives will be helpful.

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