A couple of weeks ago, I talked about being the top graduate in Production and Operations Management in my class and earning the Production Management key for my trouble. One of the things that attracted me to the major was that it involved a lot of statistics and number-crunching, In fact, the classes in the major were all given the designation of OMQM, for Operations Management and Quantitative Methods. I couldn’t have cared less about the Operations Management side, it was the Quantitative Methods that I was really interested in. These included the courses in Statistics and Data Processing (the old name for Information Technology, or IT). You can take the boy out of Math, but you can’t take Math out of the boy.
Problem was, there was no real career path for statisticians at the time. I looked into actuarial science, but that required a lot more math than I had, and I really didn’t want to go there. I considered becoming a baseball statistician, particularly with the advent of sabermetrics, which created a need for statistics that was above and beyond batting average and ERA, but that would have required moving to New York, where the offices of the major leagues and most of the companies that computed those numbers were located. There was always government work, and… just no. So I moved into Data Processsing and had a good career there, as a programmer, technical support specialist, database administrator, and trainer.
Lately I’ve been seeing a lot of ads on Instagram (which has a lot of ads, anyway) for a relatively new field called Data Science, part of the ever-growing field of Big Data. The Internet has made it possible for businesses and government entities to collect massive amounts of data, and Data Science looks for ways to attach some meaning to the numbers. Granted, it’s a scary prospect, knowing that there is so much data floating around out there, some of which has to do with each of us, evaluating areas of our lives that we didn’t even know existed, and many of the ethical considerations have yet to be evaluated. Still, the more I see about it, the more interesting it becomes. It’s a very new field which evidently didn’t even exist until a few years ago; still, I have a good background in statistics and statistical methods, and it would be great to get in when the field was relatively new.
So, that’s what I’d do: if I had to choose a new career for myself, I’d be looking at Data Science.