*A, A-, B+, B, B-, C+, C, C-, D+ and D*. These are all passing grades.

*A- is 3.7, B+ is 3.30 and B is 3.0 on a scale of 4.*

My overall GPA is :

**3.57**

GRE or GMAT:

**Will be taken.**

Bsc. Thesis:Sexual Health Economics in Emerging countries ( It includes Panel Data analysis of the data of 40 country, it was a quantitative research,

Bsc. Thesis:

**I got A**).

**My math classes are :**

*Calculus 1*(

**A-**),

*Calculus 2*(

**A**),

*Linear Algebra and Differential Equations*(They are in the same course 8 weeks Linear Algebra up to Diagonalisation of Matrices and Applications in Linear Algebra and up to Variation of Parameters in DE. I got

**B+**),

*Mathematics for Economists*(Euclidean vector spaces, Karush Kuhn Tucker optimization

**, A-**)

*Probability and Statistics 1*(It is written as Succesfull in my transcript because of the pandemics but I passed it with

**B+**),

*Probability and Statistics 2*(

**A**),

*Econometrics 1*(

**B+**),

*Econometrics 2*(Time series models, Arch, Garch

**A-**)

**My economics classes are very calculus oriented:**

*Macroeconomic Theory 1*(

**A**),

*Macroeconomic Theory 2*(

**B),**

*Microeconomic Theory*(

**A-**),

*Introduction to Accounting*(

**A-**),

*Introduction to Management Science*(

**A-**),

**Programming and Finance courses are:**

*Introduction to programing with MATLAB*(

**B+**),

*Computing and Programming with Python*(We learned searching,sorting algorithms, OOP, Matlab, Numpy, loops, I got

**B+**),

*Applied Data Analysis with R*(We learned both the theory and application of ML models such as logistic regression, data transformation, KNN and support vector machines, I learned EDA and data analysis methods, in the exams we implemented the methods we learned, unfortunatelIy I got

**B**),

*Corporate Finance*(

**A-**),

*Introduction to Financial Engineering*(We started from binomial models and came to Black Scholes, heston volatility model, we learned the application of stochastic calculus in finance, I got

**B+**),

**Internships**: One at an insurance company, one at a startup where we tried to build a market neutral portfolio composed of cryptocurrencies, I sharpened my Python skills there. I worked 2 months. And my third internship was a month in Ministry of Treasury and Finance of my country. It did not include much quantitative finance but I learned data visualization tables such as Power BI and ggplot2 deeply.

**Reference letters:**I can get a very concrete letter from my statistics professor, he knows me very well, he can talk about my statistics and programming (generally R and Stata) skills very well. I can also get a letter from my advisor in the Treasury of Finance, he can talk about my data analysis skills deeply. He has a Msc from University of Columbia. I can also get a letter from my corporate finance proffessor. He knows my quantative skills and my eagerness to learn finance.

**Target Schools and deparments**:

University of Chicago Quantitative Finance,

Columbia University Quantitative Finance,

ETH Zurich Quant Finance,

ETH Zurich Data Science,

ETH Zurich Statistics,

EPFL Financial Engineering,

EPFL Data Science,

EPFL Statistics,

Wien University of Economics Quantitative Finance

I think courses and skills I accumulated during my 3 year bachelors prepares me well for each of the 3 different msc programs. I am interested in math and programming, msc in statistics or Data Science also appeals to me a lot. I am indifferent between finance, DS and statistics, each of them makes me happy. I would like to know about my chances. Thanks for your comments, suggestions and your time.