Some suggestions from Mathematics student who pursued a MMOR from the UBC Center for Operations Excellence 2013
Some thoughts on graduate studies in operations research at the UBC Center for Operations Excellence from a former UBC Mathematics undergraduate who has just finished the program (in 2013) and is now employed in industry:
As a math student, you are probably well prepared for most of the technical aspects of the program. As far as course selection is concerned, operations research is an interdisciplinary field, and in general, my feeling is that a breadth of intermediate/upper level courses spanning mathematics, statistics, and computer science is probably more useful preparation than a more specialized focus in one area. If you have taken some intermediate level courses in statistics, optimization, and stochastic processes in your undergrad however, you will have previous exposure to a lot of the concepts that make up the technical parts of the curriculum.
A big part of the program is teaching students professional skills as well as technical skills, and this comes across even in the math and statistics courses. Nearly every assignment you have will involve working with others, and producing either a technical report or a slide presentation explaining your findings. In retrospect I think this is probably a very good approach because in a professional setting you will need to be able to work as part of a team, and you are definitely going to need to be able to explain your findings to other people who usually do not have the same background that you do.
Rather than writing a Master's thesis like in a research focused degree students in the MMOR program work on a consulting engagement with an industry partner. This means that if there is a particular research topic you are interested in investigating, the MMOR program may not be the best choice, as the nature of the industry partner's problem is going to determine what sort of techniques and approaches are most appropriate.
Like any real-world engagement, there is also a lot of work involved that is not the fun math bits. Expect to spend a considerable amount of energy dealing with some or all of the following depending on the nature of the project: Managing client expectations and relationships; Collecting and/or cleaning data; reporting and documenting your work; troubleshooting software problems, training users, and writing user manuals.
That being said, I found the industry project was great experience. Basically, you will be taking a problem that is probably not well defined mathematically in a context that you probably don't know much about, figuring out what you can say about the problem and what you can reasonably achieve in the time you have, then working to accomplish the goals you've agreed on with the industry partner.
For students interested in working in industry, the program is a very good choice. The COE has a good reputation with local industries that use analytics, and because the COE showcases student work every year in order to get local businesses interested in working with them on future projects, the industry projects usually bring students in contact with a number of potential employers interested in hiring analytics professionals. Many students receive job offers before graduation. If there is a particular industry that you are interested in, such as healthcare, or commercial aviation, it may be a good idea to tell this to directors at the lab who decide which students will work on which industry projects.
For Students Considering Doctoral Studies
While some students do go on to do doctoral studies, an MMOR is a professional degree, and there are probably more natural vehicles for going on to do a PhD. Part of the reason for this is that your project technical report is not a thesis. It might contain sensitive information for the industry partner you worked with which they do not want you to share, and even if it doesn't, while the work you provided may be useful and novel for the industry partner, it may not be especially ground-breaking in the academic community.