Tom Davenport has an excellent mid-lenth piece out in the Harvard Business Review about how data science is the new sexy job. Tom has been writing about this for quite some time. (HBR) Of particular note was his description of the Insight Data Science Program, which is a post-doc Silicon Valley feeder five week training program. (IDSP)
What is clear is that this relatively new discipline is still nascent and does not have a formal academic domain yet. In truth, that makes it more interesting, as it brings in talent from the whole spectrum of quantitative disciplines.
Here’s an excerpt:
What kind of person does all this? What abilities make a data scientist successful? Think of him or her as a hybrid of data hacker, analyst, communicator, and trusted adviser. The combination is extremely powerful—and rare.
Data scientists’ most basic, universal skill is the ability to write code. This may be less true in five years’ time, when many more people will have the title “data scientist” on their business cards. More enduring will be the need for data scientists to communicate in language that all their stakeholders understand—and to demonstrate the special skills involved in storytelling with data, whether verbally, visually, or—ideally—both.
But we would say the dominant trait among data scientists is an intense curiosity—a desire to go beneath the surface of a problem, find the questions at its heart, and distill them into a very clear set of hypotheses that can be tested. This often entails the associative thinking that characterizes the most creative scientists in any field. For example, we know of a data scientist studying a fraud problem who realized that it was analogous to a type of DNA sequencing problem. By bringing together those disparate worlds, he and his team were able to craft a solution that dramatically reduced fraud losses.
Perhaps it’s becoming clear why the word “scientist” fits this emerging role. Experimental physicists, for example, also have to design equipment, gather data, conduct multiple experiments, and communicate their results. Thus, companies looking for people who can work with complex data have had good luck recruiting among those with educational and work backgrounds in the physical or social sciences. Some of the best and brightest data scientists are PhDs in esoteric fields like ecology and systems biology. George Roumeliotis, the head of a data science team at Intuit in Silicon Valley, holds a doctorate in astrophysics. A little less surprisingly, many of the data scientists working in business today were formally trained in computer science, math, or economics. They can emerge from any field that has a strong data and computational focus.