Barely two days after setting up for State U, I received a resume in my email box. I was at first happy to notice it was from a student. It's gratifying to see that job seekers are attentive to CRSM updates. But when I looked at the attached resume, I noticed he was to earn an advanced degree in educational psychology.
My first reaction was “What the h---'s educational psychology?” My second was “How did I get this resume? Didn't I write a tight enough job description?” I sure thought I'd made it clear OpenBI's looking for students with mathematical, programming and business backgrounds. We're not in the market for “soft” social science applicants.
As I moved the correspondence to the trash bin, though, I noticed the phrases “quantitative methods,” “program evaluation,” “statistical analysis,” “computer science” and “machine learning,” I must admit I was confused. What was this candidate, a psych major or a quants head? It turns out, both. I'm sure happy my trash request was delayed.
Big State U is the University of Wisconsin, Madison, one of the nation's top universities. I love interviewing at UW. Besides visiting a great school in a hip and livable city, I now get to see my student son when I recruit there. And, as luck would have it, it also appears UW has the top-ranked grad school program in Educational Psychology, offering both MS and PhD degrees with an emphasis in Quantitative Methods. QM, one of four departmental specialties, seems an unlikely area of emphasis for education, but what do I know?
Intrigued by my “education” I dug a little deeper into the EP website and continued to like what I found. The QM sub-specialty certainly attracts top quants students. Over the past six years, the average undergraduate GPA for admitted QM grad students is 3.5; the average GRE Math score, 750 out of 800 -- impressive indeed.
Program foci include a strong foundation in mathematics and statistical theory; emphasis in applied statistics and psychometrics; the application of diverse quantitative methods in a wide variety of contexts; and the conduct of high-quality research – all skills highly pertinent and transferable to BI. “The study of quantitative methods takes advantage of the range of resources at the UW-Madison and includes course work in statistics, mathematics, and computer sciences .... the Quantitative Methods area offers two major specializations: Statistics and Measurement. Through course work in the departments of Statistics, Mathematics, Computer Science and in other units of the School of Education, students can acquire the knowledge and skills to be professionally successful.” I like.
An ideal BI candidate from QM for OpenBI will have completed coursework in advanced statistics and experimental design in addition to the required statistical core. A sequence of courses in measurement and research design is also on the BI mark – our discipline can certainly use an upgrade to what often passes as BI research today. The study of Program Evaluation is likewise germane to BI. PE is to education and social programs as performance measurement is to business. Just as PE seeks to discern the causes and effects of social programs, PM similarly looks at the inputs and outputs of business strategy. And extending one's statistical reach through a machine learning sequence taught by the Computer Science department is now almost mandatory for students seeking careers in predictive analytics. Throw in the capability to manage and program with data, and I'd be sold on this curricula.
I emailed the candidate that I'd save a slot for him on my October docket. I also plan to contact the QM faculty to see if I can establish a recruiting dialog. I'd like nothing better than to tap another reliable source of top quantitative talent to help OpenBI grow.