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Trying to figure out what I should get my masters in

  1. Dec 9, 2015 #1
    Hey PF! So I have a pretty weird situation, here is what's up:

    I am 2 semesters away from finishing either a math OR physics degree. I recently came to the conclusion that I want to make a lot of money and am trying to figure out what I want (or am able for that matter) to go to graduate school for, and therefore what kind of classes I want to focus on in my last 2 semesters as an undergraduate.

    One thing I was thinking was finishing up my math degree and at the same time take statics and then dynamics, after which I would want to try to go get a masters in mechanical engineering. Anyone have thoughts on this?

    Another thing I was thinking is finishing up my math degree and at the same time taking introduction to probability and then mathematical statistics, preparing me for a masters degree in statistics. Anyone have thoughts on this?

    The only CS class I have taken is CS 170, introduction to python >.<.

    Anyway, if anyone has any ideas on what I should do to make money, let me know :-).
  2. jcsd
  3. Dec 10, 2015 #2
    I have some thoughts for you. Where I work, there is something like 50:1 ratio between engineers and statisticians. That is a ballpark estimate with wide error bars, but something to keep in mind. On the other hand, there is a really big difference between the number of qualified individuals seeking such positions. My recommendation to you if you want to game the system, which is my interpretation of your question, is to find out in which field your odds might be best. I might also recommend to you that sometimes you can get a good result by being a big fish in a small pond.

    As for your masters degree path, in my opinion, you will have a shorter path to a degree by choosing stats, as that is less likely to require you to complete a bunch of foundational coursework to even get started than mechanical engineering. Given that the monetary payoff of a master's degree is not related to how long it takes you to finish, except insofar as you get to the job market sooner or later, it is in your best interest to finish as fast as possible.

    Finally, if you would like remunerative employment, my recommendation to you is to be highly employable, and use all of the resources available to you to become so. There is a great deal of advice on how to do this all over this board, but in short, you need to take advantage of your friends, relatives, and professors to get connections with places that pay money for work. You need to be hard-working and reliable. You need to get along well with others, especially ones you dislike. You need to be willing and able to do things that someone else is willing to pay for. Getting a degree may be less important than these other things, unless it serves as a credential in a field you want to enter.
  4. Dec 11, 2015 #3


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    To the OP:

    I finished with a Masters in statistics after completing my undergraduate degree in math and I've been working as a biostatistician in the pharma/biotech sector for the past 12 years (and worked as a statistician in other industries for 3 more years). My feeling is that the coursework that you've taken thus far (plus further coursework that you intend to take in probability theory and mathematical statistics) will prepare you well for a future masters degree in statistics. As far as employability is concerned, a masters in statistics will open up opportunities for you in areas like data science, biostatistics, etc.

    My advice for you beyond what Ben Espen has posted is to really take the time and effort to build up your programming skills, either through more courses in the CS department or through independent learning (including studying through Coursera or other online courses), since it is expected that statisticians should have at least basic programming skills to conduct their analyses (in fact, anyone in any quantitative field should have at least basic programming skills). I would also recommend that you study how to program in SAS and R, since these are programming packages that statisticians use most frequently. Knowing some SQL wouldn't hurt either. You should be able to find resources on these on the web (if I find good links, I'll post these here).
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