I always considered "MS/OR" a hybrid that shares the underlying philosophy of the scientific method and as such is malleable and can be extended to any methodologies and problem sets. My training, in the mid 70's consisted of non-statistical methods such as linear programming and statistical methods of queueing theory and Markov chains. The curriculum would be comfortable with glomming these and other methods in the field. I'm more comfortable now with the designation of "data scientist" which emphasizes this underlying philosophy.