In Growing Field of Big Data, Jobs Go Unfilled

(Chicago Tribune/MCT) -

Professionals in big data are big deals in today’s largely sluggish U.S. job market.

The demand for talent capable of gleaning useful information from businesses’ increasingly large and diverse data sets – generated by sensors, electronic payments, online sales, social media and more – is outpacing the supply of workers.

Take Enova International, which analyzes more than two dozen data sources to determine, in less than 10 minutes, whether an applicant will qualify for one of its three-year, $10,000 loans.

In the past three years, the growing Chicago online lender has doubled the size of its analytic team to 25 people, and next year, it would like to increase it by 50 percent, said Adam McElhinney, Enova’s head of business analytics. “There’s a shortage of talent that we’re looking to address,” McElhinney said.

By 2018, the United States might face a shortfall of about 35 percent in the number of people with advanced training in statistics and other disciplines who can help companies realize the potential of digital information generated from their own operations as well as from suppliers and customers, according to McKinsey & Co.

That deficit represents more than 140,000 workers, the consulting firm estimates.

Workers in big data are hard to come by in the short term. A recent survey by CareerBuilder – an affiliate of Tribune Co., which owns the Chicago Tribune and is a partner in McClatchy-Tribune News Service – found that “jobs tied to managing and interpreting big data” were among the “hot areas for hiring” in the second half of 2013.

“There aren’t enough of them. Period. End of story,” said Linda Burtch, founder of Burtch Works, an Evanston, Ill.-based executive recruitment firm. “The demand for quantitative professionals has grown so across industries that there aren’t enough kids coming out of school studying math and statistics.”

As a result, about half of Enova’s data analysts have visas or green cards.

Historically, Enova typically hired people with degrees in statistics, computer science and industrial engineering, but it has broadened its potential talent pool to include people with backgrounds in astrophysics and computational chemistry.

Enova, a unit of Texas-based Cash America International Inc., visits with Northwestern University and the University of Chicago several times a year, recommending that they adjust their curriculum to help turn out graduates with the skills for big data.

“Over the past five years, there has been a convergence of data analysis and computer science,” McElhinney said, noting that big data requires proficiency at both. “Five years ago, that was not the case.”

On Oct. 11 at the University of Chicago, Enova, which has more than 1,000 Chicago-area workers, is sponsoring a “data smackdown,” in which it will provide students with a data set and business case; the students will have six hours to make recommendations. Meanwhile, IBM said Aug. 14 that it has now partnered with more than 1,000 colleges and universities, including those at Northwestern and DePaul, to try to narrow the skills gap on big data.

Thanks partly to advances in software and database systems, companies find it easier to capture, store, crunch and share the data in ways that help their businesses serve customers, predict their behavior, innovate, improve productivity and cut costs. The computing power of the average desktop computer, for example, has risen by 75 times from 2000 to 2013, McKinsey said.

Big data pays well. Median base salaries for non-management workers is $90,000, according to a 47-page Burtch Works report, published in July, that surveyed 2,845 of the quantitative professionals in the firm’s database.

Nearly 9 of 10 big data professionals have at least a master’s in a quantitative discipline such as statistics, applied mathematics, operations research or economics, according to Burtch Works.

At companies, they work in such areas as analytical database marketing, analytics management and business intelligence. Nearly 40 percent are foreign citizens, Burtch Works found in its study.

Nine out of 10 quantitative professionals are recruited over LinkedIn at least once a month, Burtch said.

“Candidates with a strong breadth of knowledge in big data are challenging to find,” said Rona Borre, chief executive of Instant Technology, a Chicago-based talent management firm.

She said junior-level professionals in big data can start out earning $80,000, with senior technicians making as much as $140,000.

Big data professionals are also becoming more important to insurance companies, which need help sorting through and learning from data to provide better services and savings for their policyholders.

For example, Progressive Corp.’s Snapshot device, which is installed in the car and collects driving data, has pulled in more than 8 billion miles of driving data, a number that increases by the second.

As such, Progressive has “become much more proactive” about finding big data talent, including having a staff of “sourcing specialists” who home in on finding people with big data skills, said Adam Kornick, Progressive’s big data and analytics business leader. “As part of our recruiting efforts, we spend a lot of time highlighting Cleveland as a great place to live and work.”


  • Big data professionals: Individuals who can apply sophisticated quantitative skills to data transactions, interactions or other behaviors to draw conclusions and recommend actions. They’re distinguished by the sheer quantity of data on which they operate, due to new ways to measure behavior and technological advances in the storage and retrieval of data.
  • Internet of Things: The ubiquitous network of sensors, cameras and transmitters embedded in devices around the world.
  • Units of measure: Gigabytes eventually become terabytes, which then become petabytes, which then become exabytes. Then it’s on to, respectively, zettabytes and yottabytes.
  • Unstructured data: Not as easily searched as the highly structured and clean data sets of, say, customer purchase histories or inventory levels. It includes blog posts, social-media feeds, GPS tracking data, online chat rooms, and most audio and video content.

SOURCES: McKinsey & Co., Burtch Works LLC