All good, but I think statistics as I understand it, is only a facet of the work involved. And the outcome or goal of their work seems generally to be the creation of a knowledge-based system for predictive analysis; to derive ontological meaning from numerical data (mostly about humans and human activity).
Not a bad article, if a little short, on wikipedia kinda captures it for me [0]:
* Assessment of the problem
* Development of a knowledge-based system shell/structure
* Acquisition and structuring of the related information,
knowledge and specific preferences (IPK model)
* Implementation of the structured knowledge into knowledge
bases
* Testing and validation of the inserted knowledge
Right, but the question is whether statistics is the most important facet of the work involved. Everything you've listed except "maintenance of the system" is part of statistics (which I'm going to define broadly as: 'what statisticians do'), and system maintenance is only missing in a "keep servers online" sense, not a "make sure that the concept we implemented remains appropriate" sense.
Not a bad article, if a little short, on wikipedia kinda captures it for me [0]:
* Assessment of the problem
* Development of a knowledge-based system shell/structure
* Acquisition and structuring of the related information, knowledge and specific preferences (IPK model)
* Implementation of the structured knowledge into knowledge bases
* Testing and validation of the inserted knowledge
* Integration and maintenance of the system
* Revision and evaluation of the system.
[0] http://en.wikipedia.org/wiki/Knowledge_engineering