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We have two closely related groups in our company. Mathematical Optimization and Data Science. I am in the optimization group, but when I query the data scientists, they seem to be doing similar things - simulation, network optimization, resource allocation and planning. I am not sure why management wants to call them data science.

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I'd guess that historically the Mathematical Optimization department has comprised "legacy" operations research people (spreadsheet modeling and decision analysis, linear and nonlinear modeling with AMPL-type tools, SAS statistics, etc) and the Data Science group is newer and more software-ish.

Am I right?

I guess so. They work with SAS and python, while we work with C++ and CPLEX on vi editor in a linux terminal.

Maybe they are just proxies for other labels, like "the good group" and "the one we can drop if our numbers don't hit expectations." I'm offering this theory as a bayesian.

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