Hi everyone,
I’m currently preparing applications for 2026 MFE/MFin programs in the UK and US and would really appreciate your perspective.
I graduated two years ago with a BSc in Mathematics and Economics from the London School of Economics. While I obtained a 2:2 overall, my final-year performance improved significantly, with Firsts and high 2:1s in quantitative and applied courses such as stochastic calculus, time series analysis, and machine learning. The Director of the Mathematics Department, with whom I have a strong relationship, has kindly agreed to provide my academic reference.
To strengthen my quantitative profile, I also took the GRE (167 Quant, 156 Verbal, 4.0 AWA). I’m considering retaking it to push the Quant score higher, but I’m unsure whether it’s necessary given my current result.
Professionally, I completed long-term internships at a hedge fund and an investment bank in quantitative roles, where I supported trading teams on risk management and index-rebalancing backtests. Alongside that, I’ve been building a strong project base — mostly in Python, applying concepts from papers, books, and discussions with practitioners. Notably, I ranked well in a DRW machine learning competition and have been developing a mid-frequency trading system for about a year. I also completed the C++ for Financial Engineering course on QuantNet, which I highly recommend for anyone wanting to deepen their low-level, object-oriented programming skills for options pricing and numerical methods.
I’m aware that most programs are cautious with applicants holding a 2:2, but given my strong university background, improved academic record in relevant subjects, professional experience, and technical projects, I’m hoping my profile remains competitive.
Any feedback on how to best position my application — or whether retaking the GRE is worthwhile — would be greatly appreciated.
Thanks in advance for your insights
I’m currently preparing applications for 2026 MFE/MFin programs in the UK and US and would really appreciate your perspective.
I graduated two years ago with a BSc in Mathematics and Economics from the London School of Economics. While I obtained a 2:2 overall, my final-year performance improved significantly, with Firsts and high 2:1s in quantitative and applied courses such as stochastic calculus, time series analysis, and machine learning. The Director of the Mathematics Department, with whom I have a strong relationship, has kindly agreed to provide my academic reference.
To strengthen my quantitative profile, I also took the GRE (167 Quant, 156 Verbal, 4.0 AWA). I’m considering retaking it to push the Quant score higher, but I’m unsure whether it’s necessary given my current result.
Professionally, I completed long-term internships at a hedge fund and an investment bank in quantitative roles, where I supported trading teams on risk management and index-rebalancing backtests. Alongside that, I’ve been building a strong project base — mostly in Python, applying concepts from papers, books, and discussions with practitioners. Notably, I ranked well in a DRW machine learning competition and have been developing a mid-frequency trading system for about a year. I also completed the C++ for Financial Engineering course on QuantNet, which I highly recommend for anyone wanting to deepen their low-level, object-oriented programming skills for options pricing and numerical methods.
I’m aware that most programs are cautious with applicants holding a 2:2, but given my strong university background, improved academic record in relevant subjects, professional experience, and technical projects, I’m hoping my profile remains competitive.
Any feedback on how to best position my application — or whether retaking the GRE is worthwhile — would be greatly appreciated.
Thanks in advance for your insights
