Hi all!
Bachelor’s degree:
Top-1 university in Economics in Russia (Mathematics and Economics major) - CGPA 7.91/10 (~3.5/4.0)
Tests:
GRE: Q170, V160
Booked CFA level I in February
Relevant courses:
Work Experience:
1.5 years full-time in top Fintech in Russia as a business-analyst/product-manager - mostly management + product analysis responsibilities
Other:
Male, final year, TA in Econometrics, won some not-so-demanding nationwide competitions in math. Was top student and got some decent scholarships in my 1st year, then started working and my CGPA dropped from 10 for 1st year to 8 for 2nd and to 6 for 3rd.
What type of recommendation I need?
1. How should I arrange these unis on reach/moderate scale? What schools should I add?
EPFL, MFE
ETH, MQF
MIT MFin
Columbia MFE
NYU MFE, MMF
UChicago MSFM
UCLA MQE
Baruch, MFE
Princeton, MFin
CMU, MCF
2. Is it viable to defend my low GPA in 2nd-3rd year by working full-time?
I am worried that low grades for more advanced math courses may be interpreted as if I am incapable of learning such subjects. Perhaps any other way beside job to prove otherwise, e.g. Teaching Assistence and Math Competition results or Recommendation Letters from professors in which subjected I did not score so well? What would you do?
I thank and appreciate any assistance.
Bachelor’s degree:
Top-1 university in Economics in Russia (Mathematics and Economics major) - CGPA 7.91/10 (~3.5/4.0)
Tests:
GRE: Q170, V160
Booked CFA level I in February
Relevant courses:
Abstract Mathematics:
Group Theory, Rings and Fields, Analysis and Elements of Topology, Modules and Vector Spaces, Elements of Mathematical Logic, Introduction to Lie Groups
Calculus:
Limits, The Riemann Integral, Improper Integrals (convergence/divergence, dominated convergence), Double and Triple Integrals, Ordinary Differential Equations, Laplace Transforms (solving ODEs with Laplace Transforms; Beta and Gamma functions)
Linear Algebra:
Diagonalisation, Jordan Normal Form and Differential Equations, Inner Products and Orthogonality, Orthogonal Diagonalisation and its Applications, Direct Sums and Projections, Generalised Inverses, Complex Matrices and Vector Spaces
Optimisation Theory:
Multi-dimensional Calculus, Constrained and Unconstrained Optimisation, Differential and Difference Equations, Optimisation Under Inequality Constraints, Kuhn-Tucker Theorem, Elements of Convex Analysis, Finite & Infinite Horizon Dynamic Programming
Financial Mathematics:
Derivatives Valuation using one-period models, multi-period models, continuous-time models. Black Scholes Model, Perpetual Options.
Python:
Pandas, NumPy, a bit of OOP
Machine Learning:
All of Elements of Statistical Learning by Tibshirani, et al.
Group Theory, Rings and Fields, Analysis and Elements of Topology, Modules and Vector Spaces, Elements of Mathematical Logic, Introduction to Lie Groups
Calculus:
Limits, The Riemann Integral, Improper Integrals (convergence/divergence, dominated convergence), Double and Triple Integrals, Ordinary Differential Equations, Laplace Transforms (solving ODEs with Laplace Transforms; Beta and Gamma functions)
Linear Algebra:
Diagonalisation, Jordan Normal Form and Differential Equations, Inner Products and Orthogonality, Orthogonal Diagonalisation and its Applications, Direct Sums and Projections, Generalised Inverses, Complex Matrices and Vector Spaces
Optimisation Theory:
Multi-dimensional Calculus, Constrained and Unconstrained Optimisation, Differential and Difference Equations, Optimisation Under Inequality Constraints, Kuhn-Tucker Theorem, Elements of Convex Analysis, Finite & Infinite Horizon Dynamic Programming
Financial Mathematics:
Derivatives Valuation using one-period models, multi-period models, continuous-time models. Black Scholes Model, Perpetual Options.
Python:
Pandas, NumPy, a bit of OOP
Machine Learning:
All of Elements of Statistical Learning by Tibshirani, et al.
Work Experience:
1.5 years full-time in top Fintech in Russia as a business-analyst/product-manager - mostly management + product analysis responsibilities
Other:
Male, final year, TA in Econometrics, won some not-so-demanding nationwide competitions in math. Was top student and got some decent scholarships in my 1st year, then started working and my CGPA dropped from 10 for 1st year to 8 for 2nd and to 6 for 3rd.
What type of recommendation I need?
1. How should I arrange these unis on reach/moderate scale? What schools should I add?
EPFL, MFE
ETH, MQF
MIT MFin
Columbia MFE
NYU MFE, MMF
UChicago MSFM
UCLA MQE
Baruch, MFE
Princeton, MFin
CMU, MCF
2. Is it viable to defend my low GPA in 2nd-3rd year by working full-time?
I am worried that low grades for more advanced math courses may be interpreted as if I am incapable of learning such subjects. Perhaps any other way beside job to prove otherwise, e.g. Teaching Assistence and Math Competition results or Recommendation Letters from professors in which subjected I did not score so well? What would you do?
I thank and appreciate any assistance.
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