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.
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.