Catherine Reynolds is principal recruiter and owner of OnBoard Recruitment Advisers, which specializes in analytics, insights and recruiting in the big data area. She has an MA in journalism from Ohio State University and a BA in English and communication arts from Georgetown College in Kentucky. She is the past president of the Ohio Recruiters Association and a member of the National Association of Personnel Services. Analytics Week named her one of the Top 200 social media thought leaders in big data and analytics.
You recruit in the big data and data science area. For companies that would like to hire someone in this area, and for people who want to get hired in these positions, how do you advise them?
My clients hire individuals with a foundation in statistics, mathematics, economics or other quantitative areas of study. Master’s degrees are the minimum for many positions. Experience with statistical packages such as SAS, R or SPSS is also required. Other technical requirements frequently found in hiring profiles are advanced Excel and SQL. Beyond this, the ability to communicate complex information to diverse audiences is also important. This includes written and verbal skills, as well as graphic visualization.
I encourage clients looking to hire data scientists to have some leeway in the hiring profiles. Everyone wants the “perfect” candidate, but there simply aren’t enough to go around. Two years ago, Gartner predicted that by 2015, 1.9 million IT jobs would be created to support big data, and for every IT job, another three jobs would be created outside of IT. However, due to a talent shortage, only one-third of the IT jobs would be filled.
Therefore, companies need to develop pipelines of entry-level talent. Build partnerships with graduate programs in your area. Hire undergraduate interns. Consider visa sponsorships. Cross-train individuals in your organization with the aptitude for learning statistical methods. Hire candidates who may not have 100 percent of the job requirements, but who align well to your culture and who have the aptitude to learn and grow with your company. Also, streamline your hiring process and develop a competitive message for “selling” the benefits of working for your company, as the market moves fast for data scientists.
Your company is based in Ohio rather than in one of the more typical high-tech areas. What are the challenges and benefits to companies outside high-tech corridors?
I recruit for companies both inside and outside of Ohio, and challenges are everywhere. Recently I took a test drive of a major job board and its analytics showed about 1,400 predictive modeler profiles in their database with more than 7,000 job postings for the same skill set. That is quite a discrepancy!
Within Ohio, most of the positions for which I recruit are in Columbus. Don’t underestimate Columbus! Columbus has been named the number one up-and-coming tech city by Forbes. Last year the Intelligent Community Forum listed Columbus as one of the ‘Top 7 Intelligent Communities of the Year.’ Columbus was the only US city on the list.
Two years ago, IBM chose Columbus to start a new big data analytics center. In partnership with IBM, Ohio State has proposed creating a new data analytics headquarters to house faculty experts and research space dedicated to synthesizing and understanding big data across numerous disciplines. With partnerships such as this, the hope is for Columbus to grow as a big data hub.
A challenge for a city such as Columbus is name recognition. For example, most people outside of the region don’t realize we are the largest city in Ohio and the 15th largest city in the US, right behind San Francisco. Benefits to living and working in Columbus include quality of life, affordable cost of living, diverse neighborhoods, excellent educational choices, our amazing arts district, and numerous parks and trails. Having the number one zoo or the number one ice cream in the country doesn’t hurt, either!
In your experience, how have you seen recruiting change, and where do you see it going in the future?
I started recruiting in October 1998. For the first six months of my recruiting career, I used a fax machine to send resumes. Job boards were in their infancy. Newbie recruiters were sent to a closet of filing cabinets where we mined paper files to gather contacts for our call lists.
Technology has changed, and will continue to evolve. Instead of mining data in the closet, we have open access to information through sites such as LinkedIn. By “we,” I mean hiring managers, recruiters and candidates alike.
Yet all that data can be overwhelming. Sometimes it takes a call from a recruiter to tell a company’s story and to engage a candidate in a specific opportunity. At its core, recruiting is storytelling. I tell a candidate’s story to a company and a company’s story to a candidate.
In the future, I see more companies creating virtual workforces for hard-to-find big data skills. The market will require it. Hiring the best talent will not be limited by geography.
I also predict companies will begin cultivating and even recruiting top STEM talent at the high school level through internship and college co-op programs.
I see data analytics applied in recruiting to predict points in time in which individuals are more likely to consider other opportunities. I am not a data scientist, but with my industry insight, I would love to participate in such an endeavor!
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