I agreed with this post up to the point where you recommend a Masters in either statistics or economics. As a former econ student/researcher, I can say that you

I agreed with this post up to the point where you recommend a Masters in either statistics or economics. As a former econ student/researcher, I can say that you should not get a MS in economics or statistics if you want to do scientific computing! 1. Both are too domain-specific, and they usually lack the technical (coding) rigor you want if you're dropping lots of $$ on a grad degree. There are exceptions -- the statsmodels.py team, for example, includes an econ guy from American University -- but they're exceptions, not rules. 2. At best, either degree will get you experience in MATLAB/SAS/Stata, which are used for data analysis. This is not scientific computing, where you'll have to convert slow models to C/C++/Java etc. Instead, if you're set on coding I would suggest a Masters in applied math or a Masters in CS with a focus on topics related to stats/ML and large-scale analysis (Bayesian inference and graphical models, sure, but don't ignore classes in numerical methods or distributed computing).