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Chem. Engineering to M.S. Stats - Please help me build my application.


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Hello everyone, my first post here :)

So I graduated from U of Washington in June 2014 and have been generally been out of school and work for the last 6 months. I've been contemplating about getting an M.S. Stats and start a career in data science and now am trying to sketch a concrete plan to build a competitive application when I apply in Dec. 2015.

I can see that my undergrad transcript doesn't make me a strong candidate at all. My GPA is so so; I don't have enough stats course as many schools require; and especially my computer skills are lacking. I touched R and Java once or twice in some sophomore class, but I can't really claim that I know them. My biggest problem is that I can't really get good LOR's from my previous professors because I was a timid student in a big school, and the my last math/stat course was so long ago.


Here is the current state of my profile.

Chemical Engineering B.S. from University of Washington.

Cum. GPA: 3.60

Relevant courses:

Calculus I, II, III, and Advance Multivariable Calculus ( Transferred credits from a community college): 4.0

Differential Equation                                                                                                                               :  3.8

Matrix Algebra                                                                                                                                        :  4.0

Linear Analysis                                                                                                                                       :  3.7

Probability and Statistics for engineering majors                                                                                    :  4.0

Intro to Java I (transferred credits from a community college)                                                               :  4.0


I haven't taken GRE yet.


My current plan is to take some grad level course in stats in the next semester at a 4-year university. It's most likely U. of Houston because it's the closest to my home and is still taking application for Spring semester (for the next 5 days, yeah...). I'll spend the summer to study and take general GRE and the math subject test. It is assumed that I'll try my hardest to get good grade in these courses and GRE, as well as to really get to know my professors and get some decent LOR's.


My top target is U. of Texas A&M. But I will apply to any school that provide stipends for M.S. students in TX, Oregon, California, and WA.


I'll really appreciate any comments and advice on my chances, my plan and how to improve it. Thank you so much in advance.

Edited by VanAnh
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You are pretty much on the right track. I graduated with a maths major and only had very limited stats background, so I was in exactly the same position when I finished my undergraduate. I guess you could either take grad level stats courses or work a stats related research job for a couple of years like myself. In my opinion, grad level coursework definitely looks more attractive if you are aiming for a Masters. I would say don't worry about the GRE maths subject test, and take a course that involves lot of programming, which is crucial for a stats program especially data science... I am no expert but I would think that stats/data science is such a interdisciplinary science so a background in chemical engineering with some stats preparation should serve you pretty well in the application process. You've got plenty of time to work on the stats, you'll be fine.

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Thank you so much for your reply Dynamic89. My confidence just went down a notch after seeing a ton of amazing profiles on this forum, your reply certainly made me feel better. Good luck to you next year :)

I also want to add that one of my major weak point is the lack of research experience or any work experience worth mentioning. I did one year-long optional project but it is completely irrelevant.

My programming is at beginning level, but I have time to work on it. I'm learning Python and R on Coursera.

Edited by VanAnh
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