- Joined
- 7/16/25
- Messages
- 3
- Points
- 1
Hey, I’m going into my third year of undergrad at a non-U.S. university (well-recognized in my country). I’m pursuing a five-year dual degree in Data Science and Finance. I have taken or will take the following relevant courses:
Calculus I-III, Linear Algebra, Discrete Mathematics, Applied Mathematics for Economics, Probability Theory, Mathematical Statistics, Bayesian Statistics, Causal Inference, Linear Methods, Multivariate Methods, Empirical Methods in Finance, Financial Markets, Corporate Finance, Portfolio Management, Fixed Income, Derivatives, Finance Theory, Financial Modeling, Algorithms and Data Structures, Databases, NoSQL Databases, Data Sources, Data Visualization, Machine Learning, Artificial Intelligence, Cloud and Parallel Computing, Big Data Architecture, Applied Data Science, Data Mining, Microeconomics, Macroeconomics, Game Theory, Market Design.
Currently, I’m working as a Research Assistant for a professor focused on Quantitative Finance, and I’m also conducting independent research related to deep learning and derivatives. I’ve done some personal trading projects, and I’m preparing to take the GRE (I plan to put in serious effort to score as high as possible, especially on Quant).
This summer, I interned at a FinTech company, where my role was more aligned with AI/ML than finance. I might also get the chance to intern part-time at a large finance firm (back office role) during the school year.
In terms of academics, my GPA is 9/10. I struggled during my first semester (got a 7 in Calculus I while adjusting and an 8 in Linear Algebra), but since then I’ve consistently earned 10s in quant-heavy courses.
I also have the opportunity to do an exchange semester at UT Austin, where I could take graduate-level finance, ML and stats classes. I’m considering it partly to give U.S. admissions committees a grading reference and show I can thrive in that environment.
My targets are MFIN Princeton and MSCF CMU.
Calculus I-III, Linear Algebra, Discrete Mathematics, Applied Mathematics for Economics, Probability Theory, Mathematical Statistics, Bayesian Statistics, Causal Inference, Linear Methods, Multivariate Methods, Empirical Methods in Finance, Financial Markets, Corporate Finance, Portfolio Management, Fixed Income, Derivatives, Finance Theory, Financial Modeling, Algorithms and Data Structures, Databases, NoSQL Databases, Data Sources, Data Visualization, Machine Learning, Artificial Intelligence, Cloud and Parallel Computing, Big Data Architecture, Applied Data Science, Data Mining, Microeconomics, Macroeconomics, Game Theory, Market Design.
Currently, I’m working as a Research Assistant for a professor focused on Quantitative Finance, and I’m also conducting independent research related to deep learning and derivatives. I’ve done some personal trading projects, and I’m preparing to take the GRE (I plan to put in serious effort to score as high as possible, especially on Quant).
This summer, I interned at a FinTech company, where my role was more aligned with AI/ML than finance. I might also get the chance to intern part-time at a large finance firm (back office role) during the school year.
In terms of academics, my GPA is 9/10. I struggled during my first semester (got a 7 in Calculus I while adjusting and an 8 in Linear Algebra), but since then I’ve consistently earned 10s in quant-heavy courses.
I also have the opportunity to do an exchange semester at UT Austin, where I could take graduate-level finance, ML and stats classes. I’m considering it partly to give U.S. admissions committees a grading reference and show I can thrive in that environment.
My targets are MFIN Princeton and MSCF CMU.
- Do you think I have a realistic shot at my target programs?
- Should I prioritize work experience (take the back office internship) or focus more on school and independent research/projects?
- Is it worth doing the exchange semester at UT Austin to strengthen my application with U.S.-based grades and grad-level courses?
- What should I focus on the most over the next year to maximize my chances?
- Any general recommendations or tips would be greatly appreciated.