If you're employing data scientists in a data rich operating environment in 2016 - yes.

The big reason for the rise of "data science" is that all operating environments are now, or will soon become, data rich.

An example: I have a friend who is a chemical engineer by training and works for E-Ink. His mandate is to improve the efficiency of the chemical manufacturing plants that produce the material. This work involves a small amount of actual chemistry, and a large amount of statistical analysis of the vast trove of sensor readings and measurements produced by the plant's operation.