A Chief Analytics Officer Speaks Out on Recruiting, Retaining Analytics Talent

Don Tennant
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If ever there was a golden ticket in the IT profession, it’s becoming increasingly apparent that a degree in data analytics may be it. It’s hard to find a “hottest IT skills” list that doesn’t have Big Data front and center. IT recruiters search endlessly for data analytics talent, and as IT Business Edge’s Kim Mays noted in a recent post, Big Data skills are becoming a must-have for senior software engineers.

With all of that as the backdrop, I recently discussed the data analytics talent landscape with Joe DeCosmo, chief analytics officer at Enova, a global financial company based in Chicago. I asked him how difficult it is to recruit and retain top data analytics talent, and what his strategy is for finding and keeping people with the skills he needs. He said the competition for analytics talent is a constant challenge.


I’ve been building and managing analytics teams for 25 years, and the demand for quantitative professionals has never been higher. Given that, my managers and I dedicate a significant amount of our time to attracting and retaining top talent. With respect to recruiting, our strategy is to have a constant and visible presence at key universities, tech fairs, and meet-ups here in Chicago and throughout the Midwest. When we aren’t actively recruiting on campus, we visit as guest lecturers and host data “smack downs”—hackathons for analysts. For experienced hires, we make sure that we attend or present at various meet-up groups, conferences and other networking events throughout the year. Of course, we also have a generous employee referral program and encourage the whole team to stay active on LinkedIn and within their alumni networks to keep a steady flow of interested candidates coming to us.

DeCosmo said this competition for talent creates additional challenges on the retention front:

Simply put, we assume that the folks on our team have plenty of career options outside of Enova. Given that, we focus on creating an engaged and enthusiastic team through challenging work, constant skills training, and a fun, collaborative work environment. We have a very comprehensive analytics on-boarding program that gets folks up to speed very quickly, and then we identify high-value projects as early as possible, so they can start driving business impact right away. We use regular tech talks for the team to share new and interesting work or skills with each other, and then we make sure that everyone has an individual development plan that aligns projects and training with their career interests. I’m convinced that as long as the team is engaged with each other and are growing their own technical and business skills, folks won’t be lured away by other opportunities outside Enova. And, of course, as engagement increases, word gets back to friends, classmates, and past co-workers, so more folks reach out to us. We become an “employer of choice” for their peers.

I asked DeCosmo how he would rate the job U.S. colleges and universities are doing in preparing young people for careers in data analytics and supplying the data analytics talent that companies need. He said there’s room for improvement, but he has been encouraged by a lot of what he has seen:

We have a short list of programs throughout the country that we feel do a great job. We make sure to keep a close, collaborative relationship with these institutions, especially during peak fall recruiting season. And while there are a number of great programs out there, there still is a lot of opportunity for our colleges and universities to grow in this space. The more traditional math, stats, and econ programs seem to be a bit slower to adjust to today’s applied, quantitative needs. It’s interesting to me that we’re finding students from other disciplines, like engineering and the hard sciences—physics, chemistry, etc.—that often have stronger quantitative skills than our traditional target degrees. 

Also, I’m enthused by the influx of new analytics degree programs—predictive analytics, business analytics, etc. But it still may be too early to tell whether they’re creating new or better analytics talent. To some, the programs seem more like a branding exercise of existing content to try to capture the “buzz” of analytics, rather than taking a new approach to developing a meaningful combination of business and technical skills. I’m optimistic about these programs, though, and appreciate the focus on prioritizing an analytics-based education.

I asked DeCosmo to what extent U.S. companies are reliant on talent from overseas to fill data analytics positions. He indicated that they’re more reliant on talent from outside the United States now than they likely will be in the future:

Any company that is building a sizable analytics group has to use talent as the core barometer for building a competitive team, and it’s certainly true for us here at Enova, as we approach 40 folks in our practice. There certainly is a lot of STEM talent coming into the work force today from outside the U.S., and in an increasingly high-stakes analytics field, hiring decisions often will and should be talent-based. That said, with a renewed focus on STEM here in the U.S. as more and more students pursue quantitative degrees and careers, I imagine we will see these opportunities become increasingly competitive for any candidate across the board.

So what are the advantages and disadvantages of being located in Chicago, as opposed to Silicon Valley or the Northeast, with respect to recruiting and retaining top data analytics talent? DeCosmo said as a lifelong Chicagoan, he loved this question:

While we may not have the buzz of the coasts, Chicago presents a palpable advantage for us. First, we have some of the greatest universities for analytics talent right here in our city, and across the Midwest. This proximity allows us to stay active and visible on campus throughout the year, as well as to recruit talented interns that then become our brand ambassadors with their friends. 

The city also has invested heavily in fostering a vibrant tech and start-up scene that is buzzing with opportunity. From the city’s own open data projects—earlier this year, Chicago was one of five winners of the $1 million Bloomberg Mayor’s Challenge for their real-time predictive analytics platform—to start-up incubators and a constant flow of tech events, Chicago is becoming a magnet for tech talent looking for options outside of the two coasts.

Of course, Chicago also offers a cultural, social, and sports scene that rivals the coasts at a much more reasonable cost. Because we pay competitively, folks are able to live here at a much higher standard than they could in Northern California or New York City. Now if we could just do something about our winter.

I noted that IT security is also a very hot field right now, and I asked DeCosmo to what extent he sees IT security as a data analytics function and whether future IT security specialists may be more likely to have a data analytics background rather than a security background. He said data analytics is definitely playing an increasingly key role in IT security:

We are in a data-driven age where many organizations are putting their massive amounts of data to use, discovering new ways to make better decisions and drive results. IT security is an integral piece of that equation, and as organizations seek to collect and process data more quickly and more intelligently to better predict and prevent threats, I see data analytics playing a greater role in IT security. 

A strong background in security information management will continue to be most critical to a career an IT security, but there certainly is value in IT security professionals having skills in data analytics. At Enova, our IT risk team is a distinct function, and they are constantly evaluating new ways to detect and prevent threats, including using data analytics, and they often collaborate with our analysts on reporting efforts. I see IT security professionals looking to further integrate analytics into their role, both through cross-departmental collaboration and development of data analytics skill sets, but their skills specific to security information management will remain paramount.



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