According to McKinsey & Company, U.S. companies and government agencies will be facing a shortage of up to 190,000 "skilled" data scientists and 1.5 million managers and analysts who are capable of strengthening decision-making from the use of Big Data. To meet the demand, U.S. colleges and universities will need to increase the number of graduates with these skills by up to 60 percent, according to McKinsey. That poses a big problem for companies that are looking to bolster their use of customer and other types of data for gleaning actionable insights that can be applied to customer and business strategies.For most companies and government agencies, this demands inventive approaches to recruiting, staffing, and training. One company that's marching forward is Epsilon. Last year, the company hired 150 college students and began training them in data science. As Epsilon president Andy Frawley explained to me at the DMA2014 Annual Conference & Exhibition last week, the company recognizes the value of fanning out beyond traditional data science majors.
While Epsilon does recruit college students with computer science and analytics backgrounds from schools such as Boston College and Boston University, it also evaluates students who have majored in liberal arts and other courses of study who have demonstrated a strong aptitude for mathematics and/or computer science in their coursework.
There are a few benefits to taking a broader approach to recruiting. Epsilon has found that it can take students and graduates with strong math skills and train them to become analytically focused.
Plus, it's a lot more cost-effective than fighting a talent war for existing data scientists.
"If you try to hire people four years out of college with these skills, they cost a fortune," says Frawley.
In order to address the burgeoning data science skills shortage, companies need to be both practical and imaginative. What are some other steps that organizations can take to build their data science skills bases?