A career path that began with studying infectious diseases and led to analyzing terabytes of game data may seem a circuitous route. For Brendan Burke, though, the applied math skills he picked up as an undergraduate biology and political science major, the programming skills he added as a bioengineering graduate student, and his use of the two as a research scientist led to a job in the booming IT field of data science.
"A lot of the skill set I developed very specifically for biology could be applied in very commercially viable ways," says Burke, who earned both of his degrees from Stanford University and worked at the California school as a scientist. As head of player science at Playnomics, a Silicon Valley company that uses game data to develop player analytics, the math and computer science skills he used to determine how many touch points a virus requires to spread across a population now help him understand how people interact with games. "Something in data science gets your creative juices flowing when you see something that you built for an entirely different purpose can be used in all of these other ways," he says.
Data science also excites companies that want to use the data they've amassed to make strategic decisions that will benefit the bottom line.
A range of industries are using data to guide business decisions and bring in revenue, says Laura Kelley, a vice president at technology staffing firm Modis. "Companies are using this information to launch products and services. Whether it's what customers are buying, what products or services get the better ROI, [data] comes into strategic decisions."
Businesses, though, are struggling to find employees to handle big data, the term assigned to gathering and analyzing massive quantities of information. This field is relatively new to enterprise IT and although many companies are exploring data science programs, the necessary talent is still maturing, say technology and staffing executives.
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This places people with applicable skills in demand now and in the future, say hiring experts. The U.S. faces a substantial shortage of workers with data science skills, according to a much-talked about report published last year by consulting firm McKinsey and Company. The report predicted that by 2018 the country will lack 1.5 million analysts who can make strategic decisions using big data and between 140,000 to 190,000 workers with the proper data-processing technology skills.
"There [will be] more career opportunities in the future for this type of strategic analysis," says Kelley, who has seen the business intelligence analyst job change into a data scientist position in the last 18 months. "We've always used information but not to this level. With the amount of data companies are capturing on everything and everybody it's just amazing what can be done with that."
Colleges have realized the need to train people for those careers and are developing degree and certification programs targeting undergraduate and graduate students as well as IT professionals. To address immediate data-science staffing needs, which include technical and business roles, companies have adopted assorted tactics.
To handle the more than 100TB of data processed each week by BrightEdge, a San Mateo, California, startup that helps companies manage their search engine rankings, CEO and founder Jim Yu wants data workers who grasp the entire scope of big data processing.
People know how to query databases, but there is "an extra layer of understanding" when handling large data sets, which at BrightEdge includes tracking data on more than 150 billion URLs. Experience working with traditional SQL relational databases helps, but big data's scale requires a different processing mindset, he said.