Well, I would posit that the majority of data science positions are in advertising and marketing optimization. I would believe that 'global food security' may be more important than social media analysis, as the original posted speculated.
Not to belittle the meaningful point, but becoming a "data scientist" at a startup or large corporation that makes their money by advertising is analogous to becoming a 'quant' on wall-street in the 80's. You have to be in it to make money, rather than caring about the types of data the developed algorithms are applied on.
I mean, developing a new algorithm for data analysis could be just as important to the OP as analyzing bio data to forecast some sort of disease is to someone else.
Actually advertising and marketing optimization is a very critical problem that hasn't been completely solved yet, especially when privacy concerns are taken into consideration. It is critical towards keeping the Web free and create a more inter-connected economy. While this will obviously have the side-effects of "frivolous" analytics, there is indeed a dearth of enough hybrid practitioners-researchers in data science today. It will probably saturate in 5-10 years but I'm no analyst to predict that.
Not to belittle the meaningful point, but becoming a "data scientist" at a startup or large corporation that makes their money by advertising is analogous to becoming a 'quant' on wall-street in the 80's. You have to be in it to make money, rather than caring about the types of data the developed algorithms are applied on.