Hello everyone - I've been considering MFE programs for 2025 and wanted to get a sense of where my weakness lie and what programs I'm likely to be admitted to. I plan on taking some prep courses in C++ soon.
Education: Top 3 Canadian Uni (Masters), Mediocre Canadian Uni (Bachelors)
Major: Mathematics / Actuarial
Minor: Computer Science
GPA: 4.0/4.0 (Masters) / 4.1/4.3 (Bachelors)
GRE/GMAT: Haven't taken yet
Coursework:
- Wrote Master's thesis on properties of solutions to stochastic differential equations, Bachelor's honors paper in probability (mainly inequalities)
- Math: Calculus (single-variable, multi-variable), linear algebra, real analysis, number theory, numerical analysis (one course on interpolation, another mostly PDEs)
- Stats: Various probability courses (Calculus based, Markov chains, measure-theory based), various stats courses (hypothesis testing, regression, time series, simulation, Bayesian stuff, other things I can't recall)
- CS: Object Oriented Programing (Java), Data Structures & Algorithms, Machine Learning, Theoretical Comp Sci
- Finance: Actuarial math (annuities / bonds / immunization, insurance, life contingencies), one actuarial exam (covering topics such as Call-Put parity, Binomial Pricing model, Black Scholes, Exotic options, CAPM, Efficient Market Hypothesis)
Languages: Python, R, SQL, some Java/C++/SAS/VBA
Experience: Just over 1 year full time (currently employed) in an actuarial/data analytics/data science role (looking at insurance claim data, performing analyses/summaries/visualization with lots of Python/R/SQL, some work with models like XGBoost), 1 internship (4 months + 9 months part time after) at the same role as the previous, 2 internships (3 months + 4 months) at as a programmer (C++) working on specialized actuarial software
Research & Project: Thesis based Masters, no publication
Other EC: TA for 4 different courses (3 calculus + 1 stats) during Masters, several actuarial exams
Thanks everyone!
Education: Top 3 Canadian Uni (Masters), Mediocre Canadian Uni (Bachelors)
Major: Mathematics / Actuarial
Minor: Computer Science
GPA: 4.0/4.0 (Masters) / 4.1/4.3 (Bachelors)
GRE/GMAT: Haven't taken yet
Coursework:
- Wrote Master's thesis on properties of solutions to stochastic differential equations, Bachelor's honors paper in probability (mainly inequalities)
- Math: Calculus (single-variable, multi-variable), linear algebra, real analysis, number theory, numerical analysis (one course on interpolation, another mostly PDEs)
- Stats: Various probability courses (Calculus based, Markov chains, measure-theory based), various stats courses (hypothesis testing, regression, time series, simulation, Bayesian stuff, other things I can't recall)
- CS: Object Oriented Programing (Java), Data Structures & Algorithms, Machine Learning, Theoretical Comp Sci
- Finance: Actuarial math (annuities / bonds / immunization, insurance, life contingencies), one actuarial exam (covering topics such as Call-Put parity, Binomial Pricing model, Black Scholes, Exotic options, CAPM, Efficient Market Hypothesis)
Languages: Python, R, SQL, some Java/C++/SAS/VBA
Experience: Just over 1 year full time (currently employed) in an actuarial/data analytics/data science role (looking at insurance claim data, performing analyses/summaries/visualization with lots of Python/R/SQL, some work with models like XGBoost), 1 internship (4 months + 9 months part time after) at the same role as the previous, 2 internships (3 months + 4 months) at as a programmer (C++) working on specialized actuarial software
Research & Project: Thesis based Masters, no publication
Other EC: TA for 4 different courses (3 calculus + 1 stats) during Masters, several actuarial exams
Thanks everyone!
