Profile Evaluation for MFE/MSCF

[desperate_quant]

Hi all

Please help me evaluate my profile for MFE/MSCF programs. I have specifically planned my academic career to be into quantitative finance someday. There is nothing I want more than to get into good financial engineering program.

Work Experience

Data Science Role (Senior Analyst) May 22 -Present
> Conducted data analysis and modelling on large datasets to generate insights, identify trends and patterns in customer behavior, and provide risk scores to clients.
> Designed and maintained data pipelines, SQL databases, and large Python codebases for modelling and deploying solutions across various clients
> Developed and optimized machine learning algorithms, including decision trees, random forests, and gradient boosting models, to predict risk scores

Risk and quantitative Analysis Internship (4months)
> Worked at a buy side (mutual fund) firm researching on factor investing strategies. Created long-short strategies identifying stocks using machine learning models. Used fundamental data of all the stocks comprising BSE200 index and outperformed index by 38% in three year period (out sample data).

Education

Indian Institute of Technology (Tier 1 college India) - M.sc Operations Research - GPA 7.2/10 - Relevant Courses - Probability and Stochastic Processes, Mathematical Optimization, Linear System, Markov Chains and Queuing Systems, Game Theory, Introduction to Machine Learning, Markov Decision Processes, Data Structures

Bachelor in Mathematics and Statistics - GPA 63/100 - Relevant courses- Differential Calculus, Real Analysis, Vector Calculus, Numerical Analysis, Probability, Hypothesis Testing, Estimation

Institute of Actuaries of India (Actuarial Science) - Cleared 8 actuarial exams - Relevant Topics: Financial Mathematics, Brownian Motion and Martingales, Stochastic Calculus, Binomial Models and options pricing, Interest Rate Models,

Skills

Programming Languages: Python, SQL, MATLAB,
Libraries and Packages: Pandas, NumPy, Scikit Learn, SciPy, Prophet (Time Series forecasting)
Platforms and others: Windows, Linux, GITLAB, Advance MS Excel

GRE - 164Q, 146V, 3.5AWA

Other

> Have very good understanding of ML concepts
> solid understanding of probability, stochastics processes, martingales. Have read steven shreve's stochastic calculus for finance vol2 eights chapters.
> Good understanding of financial mathematics, bond pricing, options pricing,
> Read Hull's options future and other derivatives as a part of my actuarial exam. and spent time understanding mathematics behind the pricing theory


I understand that I did not do well in my grades and GRE. However, I am highly highly interested in finance and mathematics. I have spent last 6 years of my life studying mathematics, statistics, finance and machine learning. I only lack in my grades due to some reasons I could not avoid.

 

[MikeLawrence]

Grades aren't in the desired range, you're right. But you have good experience, and the actuarial exams prove you can pass a test. The GRE probably should improve a bit, but there isn't really anything here disqualifying you. If you can prove that you know the knowledge thoroughly now then the grades don't matter as much, especially if you had good reasons for why they were low.

Write a good essay explaining why you want to study these things at this program, and perform well in interviews, and I don't see why you wouldn't have a good shot at many programs.

Someone who is slightly older in Quantnet years, feel free to comment on this.

 

[desperate_quant]

Grades aren't in the desired range, you're right. But you have good experience, and the actuarial exams prove you can pass a test. The GRE probably should improve a bit, but there isn't really anything here disqualifying you. If you can prove that you know the knowledge thoroughly now then the grades don't matter as much, especially if you had good reasons for why they were low.

Write a good essay explaining why you want to study these things at this program, and perform well in interviews, and I don't see why you wouldn't have a good shot at many programs.

Someone who is slightly older in Quantnet years, feel free to comment on this.

Thank you so much. Its's really a comfort hearing one good thing about the profile.