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Data Scientists: Does Big Data Hype Equal Big Data Salaries? Posted on Jul 17 - 2017

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As the author Ethel Watts Mumford once said, “Knowledge is power, if you know it about the right person.” Depending on the organization, “the right person” might be customers, clients, suppliers, employees, students, competitors, or cybercriminals. The definition might vary, but the burning desire to know who, what, where, when, how, and why is ubiquitous and shows no signs of abating anytime soon. That’s where data scientists come in.

Burtch Works tracks trends in data science, and this year’s report reveals both good and bad news. The “big data” hype is driving more students to consider this profession, but not even data science is immune to the law of supply and demand.

For the first time in four years, salaries for Level 1 Individual Contributors (those with 0 to 3 years of experience) have decreased, and salaries are leveling off at other levels. However, these wages are still double, triple, even quadruple the annual salary for the average American worker.

Median base salaries and bonuses for Individual Contributors are as follows and actually exceed an MBA’s return on investment for entry-level, mid-level and even senior-level business grads:

Naomi Keller, Burtch Works’ data science recruiter, tells GoodCall®, “The limited supply of senior data science and analytics leaders to lead these teams is continuing to push their salaries upward.” Keller explains, “Although there has been an increase in the number of early career data scientists with three or less years’ experience, it is still extremely difficult to find experienced data scientists.”

While there may be an increase in the number of entry-level data scientists, Elke A. Rundensteiner, Ph.D., professor of computer science and founding director of the data science lab at Worcester Polytechnic Institute, is confident that the supply of talent isn’t close to reaching demand. “Instead, some companies that traditionally had not hired in this analysis field are now also recognizing the need to hire data scientists, and their pockets may not – in general – be as deep to be able to afford the extremely high salaries.” View More


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