The ongoing shortage of Big Data talent is a serious problem for companies whose business increasingly relies on data analytics to remain competitive. You can imagine how difficult it must be for IT staffing firms whose clients are clamoring for Big Data skills when this country’s colleges and universities simply aren’t churning out enough graduates to meet the demand. Where do you look to find those highly skilled people? Overseas? Perhaps. But what if you looked at the existing pool of IT workers who are already inside those companies?
That’s one of the approaches being taken by Collabera, an IT staffing firm based in Morristown, N.J. I discussed the shortage of Big Data talent in an interview earlier this week with Nixon Patel, senior vice president and head of the technology competency units at Collabera. When I asked him about the extent to which Collabera relies on foreign talent, like individuals here on H-1B visas, to fill these roles for its clients, I was blown away when Patel said Collabera has taken a different approach:
We know that the colleges and universities are not able to produce enough graduates with these skills. There are instances where there are very senior IT professionals who have a lot of experience under their belts, and who have made an effort in the last couple of years to learn the Big Data skills, especially on the analytics side, and employers are open to looking at those candidates. We looked at how we can innovate by training up the existing workforce—identifying current employees who have some kind of background where they can be transformed into Big Data developers, architects, and leaders, and providing them with an innovation lab and a center of excellence that offers online training in these emerging technologies. They are given access to our private cloud, with the tools and frameworks that they need, and to webinars and conferences. That’s how we’re closing this gap. We’re trying to do this laterally, because there is a mismatch between supply and demand. With all of our recruiting experience, and our networking, we still couldn’t meet the client demand. So we had to come up with something different.
Patel said Collabera is taking a new approach to internships, as well:
We’ve started internships not only for college students, but for people in the older generations who want to move laterally from their legacy IT to Big Data. We look at that as a new way of providing internships, where for three or six months, it’s a lower salary, but we provide the tools and support so they can transition from legacy IT to the new Big Data area.
Patel noted that the demand for Big Data talent has sparked a lot of innovation on the parts of some top universities, which is a boon for older IT workers:
When there’s a need, and a gap between supply and demand, there are people who are innovative enough to come up with new ways to create opportunities to develop these skills. These massive open online courses, or MOOCs, have emerged, as various universities are offering free courses in the data analytics and machine learning area—it’s being driven by leading institutions like MIT, Stanford, and Johns Hopkins. Thousands of people have access to these courses, which are of a really good standard, and are free, or almost free. This will help to close the gap.
Finally, I asked Patel what emerging skills he’s seeing relatively low demand for right now, that will likely be in especially high demand, say, five years from now. He said three things came to mind:
One would be statistical and machine learning languages, like a language called R, whose precursor was S. I think that language will be in high demand, because that’s going to be the basis for doing a lot of data analytics and machine learning. So that’s definitely something that people should have on their radar in the next couple of years. Secondly, there is a big move from older programming languages like Java and C++, which was the first course you would take in computer science. There’s a tremendous shift to languages like Python, which, although it’s not new compared to R, is being taught in 75 to 80 percent of computer science programs. Thirdly, what I think is going to be most critical, is the growing use of machine-learning algorithms, which are going to be applied across all business units, and every area you can think of, to automate things. Some of these algorithms have the ability to learn from existing data sets to create new data sets that can provide predictive analysis. In the next three to five years, you’ll see a tremendous number of jobs and opportunities in this area.
A contributing writer on IT management and career topics with IT Business Edge since 2009, Don Tennant began his technology journalism career in 1990 in Hong Kong, where he served as editor of the Hong Kong edition of Computerworld. After returning to the U.S. in 2000, he became Editor in Chief of the U.S. edition of Computerworld, and later assumed the editorial directorship of Computerworld and InfoWorld. Don was presented with the 2007 Timothy White Award for Editorial Integrity by American Business Media, and he is a recipient of the Jesse H. Neal National Business Journalism Award for editorial excellence in news coverage. Follow him on Twitter @dontennant.