What are my chances of getting into a top Quant school.

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I Graduated from University at Buffalo with a 3.81 GPA in computer engineering, although my technical GPA was about a 3.87. I have also taken 3 calculus classes, differential equations, linear algebra, statistics for engineering, machine learning and data science classes. After college, went into web development for the last 2 years and used PHP, javascript, html, CSS, SQL, and all that good stuff. I know this doesn't translate into MFE but I have done Quant projects on my own such as a algorithmic trader on Quant Connect, and I also have personal stock and crypto trading experience. I got a 166 Quant and a 157 Verbal for my GRE. I am very proficient in coding languages like Python, C++, and R and I would have no problem using them considering I do software development for a living. What are my chances of getting into the schools I am applying to? I am applying to UC Berkeley, UCLA, RPI, Chicago, Fordham, and Cornell. Am I wasting my money?
 
Ted, looking good for the home team. You have the kind of passion that it's tought to fake. short version: 1) try to get GRE to 170Q. If you got 166, you're like a question away from 170. Magoosh has very focused prep questions, adjusted to user level. 2) Try to take a calculus based probability class and a mathematical statistics class. Any school near you that has an actuarial program would have these. You'd probably get in as you are, but these two would make you very competitive. The probability and math stats (MLE, measures of unbiased, convergence, asymptotic normality) I'd say would be top priority, since you'll have a harder time making it through the program without these. Only thing worse than not being admitted is to be admitted and fail out.
- Did you check the pre-reqs for UCB? They added a bunch, and are now leading the charge. I'm not sure they are totally serious about them, as I've heard of folks getting in without several areas.
- UCB and Baruch have excellent prep programs - I especially like Baruchs. If I could do it over, I would have budgeted time / money to complete these before starting my program.
- Especially if you don't require visa support after school, you're going to be a top candidate I think. Maybe prioritize your applications a little. Why aren't CMU, NYU, Princeton in the mix? The outcomes of CMU, UCB, Chicago, UCLA, and Cornell are pretty impressive, the other schools seem to vary more.
 
Thank you Onegin, I will definitely look into the statistics classes. I have AP stat credit from high school and a statistics for engineers class credit but I agree I can try to learn more in this field. I haven't added CMU, NYU, Princeton to the list because my GRE is not good enough. UCB is slightly lower. I don't have the money to keep taking the GRE.
 
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Thank you Onegin, I will definitely look into the statistics classes. I have AP stat credit from high school and a statistics for engineers class credit but I agree I can try to learn more in this field. I haven't added CMU, NYU, Princeton to the list because my GRE is not good enough. UCB is slightly lower. I don't have the money to keep taking the GRE.
your GRE > my GRE and I'm at one of those schools. The rankings show the average, not the cut off. Worth a shot maybe. . .
 
Stupid question: what's GPA and GRE?
Not at all - too many TLA's (three letter acronyms). GPA = Grade Point Average; GRE = Graduate Record Examination, sort of the Verbal / Quantitative exam for admittance to US graduate schools.
 
Not at all - too many TLA's (three letter acronyms). GPA = Grade Point Average; GRE = Graduate Record Examination, sort of the Verbal / Quantitative exam for admittance to US graduate schools.
Thanks. And now the inevitable question 😍
What's the story with GPA, GRE, aka compelling reason, added advantage, why?
 
@Daniel Duffy - I haven't really thought about it. First and foremost, they are both filtering mechanisms. Schools and employers have more applications than they can possibly process, so they'll maybe set some GPA cut off, and boom, the pool goes from 2,000 to 1000. Then that's still a lot of crappy essays to read, so let's filter w/ GRE, and then we get down to 300, of which we can ultimately read and maybe interview 100 of those folks. These are both incomplete representations of potential. GPA tracks concientiousness more than intellect, and GRE is a very low level of math (like 8th grade), and more tests your ability to do practice tests and figure out the tricks to answer the questions quickly. But for filters, it's difficult to come up with something else that works at scale.

Then there's the rankings mess. Rankings are critical, because we only have 1 life and we really can't visit every program much less attend more than one, so we as candidates have to be very choosy in which ones we apply to. So what are the best schools? There should be some heirarchy that we can at least start from. GRE of accepted candidates then becomes a proxy for school selectivity, and the cut off for the filter above becomes a cut off to maintain some standing in the rankings.
 
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