Doing some research about jobs in data science today, I came across this Bloomberg article from July. The piece highlights the current high demand for workers with a command of statistics, and quotes Stanford Graduate School of Business economics professor Susan Athey as saying, "In most areas of the modern economy, math and statistics have never been more important." Work hours billed for staistical analysis increased by more than 500 percent in Q1 2013 vs Q1 2011. Harvard Business Review called data science "the sexiest job of the 21st century."
The Bloomberg article highlights one electrical-engeering PhD and NASA alumna who keeps getting data science job offers left and right because of her expertise in statistics. (After all, someone's going to have to figure out what to do with the 40,000 exabytes — that's 40 trillion gigabytes — of data expected to be created, replicated, and consumed annually by 2020.) This made me think of the post Bright Chief Scientist David Hardtke and Director of People Operations Josh Barger wrote on the topic. Their point? That the best way to hire a data scientist is by not searching for a data scientist — because the title as such hasn't been around long enough to furnish you many results. To find the skillset you're looking for, you're going to have to think outside that title.
Looking to hire someone who knows their way around massive data sets? Get tips from David and Josh's post here.