u/Katvat_123

Hi everyone,

I’m planning for 2027 admissions and wanted some blunt advice on how realistic my profile is for top MFE/MQF programs.

Background: IIT Kharagpur dual degree, B.Tech Chemical Engineering + M.Tech Financial Engineering, CGPA 8.61/10. Coursework includes probability/statistics, regression & time series, stochastic calculus, financial mathematics, derivatives/risk, econometrics, market microstructure, and ML.

I’ve completed CQF with 93 overall score and cleared FRM Level 1 with top quartiles. My projects are mostly around local volatility/delta hedging, ML-based trend prediction, portfolio optimization, exotic derivatives pricing, and some AI/ML work.

Long term, I’m interested in quant-style roles, but not only quant finance. I’m broadly interested in careers involving applied mathematics, statistics, AI/ML, modelling, and data-driven decision-making, whether in finance or adjacent domains.

I’ll be applying later this year to programs starting in 2027, such as CMU MSCF, Oxford MCF, Imperial MathFin, ETH/UZH QF, NUS QF, and similar programs. I’m also considering ISI M.Stat/MSQE as a backup/parallel route to strengthen my mathematical/statistical profile.

Main questions:

1. How competitive does this profile look for top MFE/MQF programs?
2. Are there obvious gaps I should fix before applying?
3. Instead of just the QF style programs in the mentioned universities, should I also look at other options like Statistics?

Would appreciate blunt advice.

Hi everyone,

I’m planning for 2027 admissions and trying to decide whether to prepare for M.Stat or MSQE at ISI. I’ll also be applying to foreign mathematical/computational finance programs like CMU, Oxford, Imperial, ETH Zurich, NUS etc. whose applications start later this year, but those programs would also begin in 2027.

My background: IIT Kharagpur dual degree, B.Tech Chemical Engineering + M.Tech Financial Engineering, CGPA 8.61. I’ve done coursework in probability/statistics, regression & time series, stochastic calculus, financial mathematics, derivatives/risk, financial econometrics, market microstructure, and ML.

I’ve also completed Certification in Quantitative Finance (CQF) with a score of 93 overall and cleared FRM Level 1 with top quartiles. My projects are mostly in quant finance/ML: local volatility and delta hedging, ML-based trend prediction, portfolio optimization, exotic derivatives pricing, etc.

Long term, I’m targeting quant-style roles in quant research/trading, derivatives/risk modelling, systematic research, or ML/data-driven investing, at firms like DE Shaw, JPMorgan, Morgan Stanley, BlackRock, etc. I may also consider applying again to foreign mathematical/computational finance programs after a few years of work if needed.

From the outside, M.Stat seems stronger for probability, statistics, inference, time series, ML, and mathematical depth. MSQE seems more economics/econometrics/finance oriented.

For my goals, which would be the better fit to seriously prepare for: M.Stat or MSQE?

Would appreciate honest inputs on curriculum fit, placements, and future signalling value.

P.S. I’m currently based out of Delhi NCR, so any inputs on Kolkata vs Delhi campus considerations for M.Stat/MSQE would also be helpful.