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Data Scientists: What You Need to Know Before Hiring One

Author: Patrick Gates | | October 9, 2013

Companies are increasingly interested in hiring data scientists to help them sort through and extract value from their growing mounds of Big Data.

What is a data scientist?

According to IBM’s Anjul Bhambhri, the person doing the job is part analyst, part artist, and must be able to bring change to an organization by analyzing multiple data sources. Bhambhri writes:

“A data scientist represents an evolution from the business or data analyst role. The formal training is similar, with a solid foundation typically in computer science and applications, modeling, statistics, analytics and math. What sets the data scientist apart is strong business acumen, coupled with the ability to communicate findings to both business and IT leaders in a way that can influence how an organization approaches a business challenge.”

According to Klint Finley at Wired, “[M]any of these math nerds aren’t as math nerdy as you might expect.” That’s a relief, since “data scientist” is arguably the sexiest job in today’s market. A data scientist may not need advanced degrees in math or science, or even computer programming skills, but they will need to be an independent thinker.

Definitions and interpretations

As James Kobielus, big-data evangelist for IBM, observes:

“Data scientists are in fact very real. They have been in existence for as long as humans have performed multivariate statistical analysis, time-series analysis, and other core approaches. And to the extent that you build statistical models and use various analytics tools to find non-obvious patterns in data, you yourself may be a data scientist.”

Kobelius says what’s changed is the profession is now mainstream:

“The catch-all term ‘data scientist’ has been around for years. […] In the past few years, analytics professionals have increasingly used the term ‘data scientist’ to refer to the convergence of these heretofore distinct disciplines with newer roles — such as behavioral analysis, sentiment analysis, and graph analysis — that have become super-hot in the era of digital channels and social media. Also, steady growth in data scientist job listings, professional forums, and academic curricula in the past several years is undeniable. Hiring trends bear this out. This is no fad.”

How a data scientist is born

Some practitioners suggest training by participating in data mining competitions, such as those hosted by Kaggle. Their elite competitors don’t have doctoral degrees; neither do many data analysis professionals. But often the best way to prepare for a career in data science is by actually doing the work.

Data scientists are in demand

More people are needed to do this work. Online help-wanted ads for data analytics jobs increased 46% since April 2011, writes Anne Fisher, contributor to Fortune. There are now more than 31,000 openings for data scientists, with salaries ranging from $73,450 to $89,750. “Demand for data scientists is definitely outstripping supply,” Andrew Jennings, chief analytics officer at FICO in San Jose, told Fisher. “We’re looking for more all the time.”

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