data science is successful now because they are applying quantitative methods to the social sciences -- problems most people think about. the average educated person can understand by using the magic of "machine learning" we can solve problems in politics, health, social issues, etc.
Nate Silver's lack of a math background works to his advantage. he realizes the bar for quantitative understanding in the public sphere is very low. whatever little bit he does, he has to explain to a room full of drunk people in 30 seconds or less. he is very good at this.
neither employers nor the public want to admit that at the end of the day SOMEONE has to be responsible for these calculations. i have a master's degree in math -- which nobody gave a hoot about (see item 5 in this article http://gigaom.com/2013/04/16/how-to-hire-data-scientists-and... ) we weren't taught how to communicate our ideas and results to the public -- in fact we were discouraged from it. that is difficult to unlearn.
i've heard of attempts to "democratize" machine learning. http://blog.bigml.com/2013/03/06/democratizing-machine-learn... articles like these are usually written by companies with a product or book to sell or distribute. what needs to be democratized is engineering based problem solving - using the powerful computers we hold in our pockets, our phones.