Data Scientists Are Sexy, The Name Matters

The job title "Data Scientist" is currently in flux. Previously, JobsNHire reported that Data Scientists have the best jobs in the United States.

They are known by many names. Maybe they're synonymous with data analysts, reports analysts, data miners and more. But why call them data scientists now? According to Datanami, what's in a name really matters.

Chris McKinlay tells Data Science that Data Scientists do not have a standardized description. "You have hiring mangers who take something that's like an analyst job and try to put a sexy name on it like data scientist." Basically, Data Scientists are people who can make strategic decision and bold products that will change the course of the company.

At the end of the day, a Data Scientist would always have the desired aptitudes, such as critical thinking, problem solving, data literacy, curiosity, creativity, communications, and computational literacy. Those personal attributes will always be in demand, Borne says, even when the next programming paradigm emerges.

Kirk Borne, the principal data scientist at Booz Allen Hamilton, sees data science as a team sport. "The data scientist's job is becoming better defined in more and more industries, though there are still many cases where organizations are casting a wide net for any type of data science expertise," Borne tells Datanami.

He goes on to say that "Nobody expects a unicorn anymore." He refers to the organization's different position players with the assigned skill sets. Now, companies cannot afford to hire one person to do one specific thing. They cannot even afford to "...hire a whole new team, there is more internal identification, recruiting, training, and development of existing staff," Borne goes on.

The demand for a Data Scientist is growing fast and companies are getting more fine-grained in how they differentiate among people who fall into different categories.

For Borne, "If I had to pick one... I would say that the gap is growing: the demand is growing faster than the candidate pool."

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