Big data is quickly becoming one of the largest industries in the world. With that growth, there is a need for qualified people to sort through all that data. That is where data scientists come in, but the problem is there is just not enough of them.
Harvard Business Review dubbed data science “the sexiest job of the 21st century.” With four million big data jobs expected by 2018 and a median salary of $150,000 dollars per year, it’s hard to argue.
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Karthik Rajagopalan is a data scientist at the AT&T Foundry in Plano, Texas. In this edition of “Gigs,” he explains what it takes to be a data scientist and gives advice to those looking to get into the field.
So what is a data scientist?
It is hard to define because the field is still evolving, but IBM, one of the biggest names in big data, describes the job as “part analyst, part artist…with a solid foundation in computer science and applications, modeling, statistics, analytics and math.”
Rajagopalan describes a day in his life as “a constant stream of getting data, looking at data, shaping data, coming up with different approaches, being creative with approaches.”
Because data science is such a diversified field, Rajagopalan says that it is difficult to give specific advice on how to become a data scientist, but he says creativity is a must.
An active imagination, he says, is the first requisite you must possess to get into the field followed closely by an extensive math background. Like most data scientists, Rajagopalan got his start in another field. He started in the semi-conductor industry after getting his Ph.D. in solid state physics and transitioned to data science later in his career.
Rajagopalan says, with the ever-changing landscape, it is very important to stay on top of the latest advancements in the field.
“Data scientists read a lot.” He explains, “We have to because a new tool comes out every day, there is a new technique to solving a certain problem, so a technique that has previously not been used for a problem gets used suddenly.”
As for the tools of the trade, Rajagopalan uses data analysis programs R and Python everyday and says they are essential elements to know.
The McKinsey Global Institute predicts, there will be a shortage of 140,000 to 190,000 data workers by 2018.
For more information about what it takes to be a data scientists, check out this info graphic by DataCamp.
If you are interested in becoming a data scientist, go to telecomcareers.net for job postings.
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