Hi, I am admitted by these two programs. My undergraduate majors are finance and math. I am currently enrolled in CFA. I want to pursue a future career in risk management and quantitative asset management. Which one would you Pros recommend? Any input will be greatly appreciated!
UVa data science vs UIUC MSFE
- Thread starter Nate Mac
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This is a Chicago Prop Shop vs NYC decision. Given that you want to do risk management not trading or HFT, you probably want NYC. UVA and UIUC are both good schools; I don't know which specific program has the absolute advantage, but UVA will help you a little more when it comes to NYC recruiting.
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Data Science is a very new discipline. What do you know about the career prospect of the UVA program? Have they graduated any student or you will be among the first to test it out?
Thank you for the advice! Do you think that graduate with a Data Science degree will help me break into risk management as a financial/data analyst?
The only thing I know about their program is that they are building connections with industry now, and every student has to finish a project sponsored by a company partner. This year is the first year, so that is why I am worried about the career of a Data Science degree. Do you have any thoughts on this? Thank you!
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There is a clear need for people with training in Big Data, data science, etc but we will need a few years so have a good picture of the degree value.
At for this specific program, there will be kinks to be worked out. I'm very interested in these new degree and would definitely closely follow its development in the next few years.
At for this specific program, there will be kinks to be worked out. I'm very interested in these new degree and would definitely closely follow its development in the next few years.
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You should read the article about Big Data by @Andrew Sheppard in QuantNet Guide. It should give you much better idea of what problems these programs try to address and the type of jobs you are trained for.
Thank you!
I'm not 100% sure. It's a new program. As usual, I am finding myself amending my advice to "What @Andy Nguyen said." This is a new program, and my drive-by analysis on programs I'm not all that familiar with (such as what I did with UVA) is to think back to how many undergrads and other students I've met from that university. Data science is also a very new field. Maybe a better answer to the question on UVA is "I don't know."
The thing about people with stats backgrounds is that we don't like to make predictions until we have data to support them, which is kind of a catch-22 for new stuff. Thank goodness the Manhattan Project was run by Physicists rather than ORFE people. If you had asked them what would happen when we detonated the Trinity warhead, they would have responded "We don't know- we don't have a sample set!" My guess is that you'll get outcomes that are on par with an MFE, but I honestly have no idea. And we're not the ones sitting 7 miles away from the bomb in the New Mexico desert, so this is an analysis that you need to conduct on your own.
UIUC will get you into the Chicago prop shops if you hustle a little and are OK going out and recruiting without a lot of handholding. UIUC will not help you get into the NYC banks where a lot of the risk management jobs are.
If you're currently working, you may consider waiting a year and applying to Rutgers. I believe Rutgers has a more established MFE program that is closer to NYC recruiting and would probably also do well in risk management. I believe they also offer some interesting data science and machine learning courses.
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Thank you so much for this detailed explanation.
GoIllini, are you referring to Rutger's FSRM here?
You're comparing two different things though there is some overlap. The important question is what do you want to do? If you're interested in building data pipelines, predictive modeling, machine learning, etc then Data Science may be the way to go. Though there is some overlap in skills, technologies and mindset required for Data Science and FE. Figure out you want to do and then optimize for that
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