Profile Evaluation for MFE 2023

[kangju]

Hi, everyone!

I am an undergraduate student who recently graduated. My school is in the top 5 schools in South Korea.

Unfortunately, I do not have work experience in finance. Instead, I have some work experience in data analytics, but I am not sure how much this would be beneficial to my resume and SoP for MFE.

I am currently enrolled in a Quantnet C++ course and pretty much enjoying the course. Will do my best to get Certificate with Distinction :D

Taking GRE soon. Not sure about the scores, but planning to take GRE until I get Q 168+, V 160+.

Below is my profile.

PROFILE​

EDUCATION​

Bachelor’s Degree

• Business Administration, Double major in Statistics
• Graduated magna cum laude, Fully Funded Scholarship
• Cumulative GPA: 3.90/4.0; Major GPA: 3.92/4.0 (FYI 3.84/4.0 in statistics)

Relevant Coursework

Mathematics

• Mathematics for Statistics (Calculus I and II excluding vector part)
• Matrix Algebra for Statistics (Materials were the same or at most analogous to Linear Algebra)
• Analysis I (Introduction to Analysis)

Statistics

• Introduction to Mathematical Statistics
• Introduction to Regression Analysis
• Introduction to Bayesian Analysis
• Introduction to Multivariate Statistical Analysis
• Introduction to Statistical Programming (Learned R)
• Stochastic Processes

Business

• Derivative Securities
• Current Topics in Finance (Equity valuation modeling)
• Business Statistics II (Basic machine learning project)

EXPERIENCE​

Data Analyst (global startup) (Aug 2021 - May 2022)​

• Involved in a data science project that measures and displays data in real-time
• Responsible for research, management, and analysis of secondary data which were utilized in the project
• Utilized Python to manage, explore, and analyze secondary data
• Communicated with global organizations

Founder and CEO (my own business) (Sep 2019 - Present)​

• Developed and operated an e-commerce platform
• Utilized Python to create an automation program that scrawls and updates data
• (Created and operated an athleisure apparel brand)
• (+ tons of stories that are not at all quantitative)

Auxiliary Police (Feb 2016 - Nov 2017)​

Competition​

Quant Investment Competition

• Researched and designed a quantitative investment strategy based on the quality factor
• Utilized Python to backtest the strategy

Also, please overview my education plan and admission strategy.

Education plan​

GRE

• Will take until Q 168 +, V 160 +
• At least Q 165, V 153 is estimated.

Math

• Currently enrolled in numerical analysis course on Coursera. Planning to finish the course until November.
• Go through the two books by Dan Stefanica on self-study: "A Primer for the Mathematics of Financial Engineering" and "A Linear Algebra Primer for Financial Engineering"

Programming

• Planning to finish the Quantnet C++ course until November
• Learn machine learning through a MOOC course or a book (after admission and throughout my master)

Finance

• Go through the option book by Hull

Admission Strategy​

Below are my advantages and disadvantages when it comes to MFE admission.

Advantages

• GPA that is not low
• Data-related work experience
• Statistics background

Disadvantages

• Not enough math courses taken
• No quant work experience
• No quant-related papers

Upon looking at the tracker data, I thought that I may not be qualified enough for tier 1 MFEs. Thus, I would be applying to 3~4 schools in the top 10, and 3~4 schools below the top 10.

Below is a presumable list of the schools.

In the Top 10

• Columbia University (Financial Engineering)
• Carnegie Mellon University (Computational Finance)
• Cornell University (MEng, FE concentration)
• University of Chicago (Financial Mathematics)
• Baruch College (Financial Engineering) (If possible)

Below the Top 10

• Georgia Institute of Technology (Quantitative and Computational Finance)
• North Carolina State University (Financial Mathematics)
• Rutgers University (Quantitative Finance)
• Stony Brook University (Quantitative Finance)
• University of Washington (Computational Finance & Risk Management)

GOAL​

Becoming a buy-side quant in the US (Not sure which would suit: trader, researcher, and risk analyst. If possible, want to become a trader.)

Of course, I know that it is extremely hard to land a job in a buy-side firm right after graduating MFE if not for tier 1 MFEs. Anyhow, I will take any detour path available to achieve the goal.

Questions​

Here are some questions that you can refer to:

1. How much do you think are the odds for me to get admitted to the schools listed above?

2. Could you recommend the best schools, if any comes to mind, that suit my profile?

3. Would my profile satisfy the prerequisite of Calculus I, II, and linear algebra? I know that it is better to ask the admission office of each university, but just checking for any insight that might help.

4. What aspects do you think should be highlighted on SoP based on my profile?

5. How do you think about applying for data science or data analytics in my case?

5.1. Are there plenty of quality jobs in the finance industry for data scientists and data analysts compared to quants?

5.2. Is it possible to become a quant trader with a data background?

6. Since I do not have any work experience, would it be better to do multiple internships or get a quant job in my country and shoot for MFE in the next year?

7. How do you think of my business experience? Will it add value to my resume? Since I did my business during working in a firm as a data analyst (fyi it was definitely legit), it is possible to delete the experience without leaving any hole in my resume.


Any further comments or advice would be more than welcome.

Thank you ahead for your precious answer :D

 

[kombuchalover]

There are a lot of questions, and I don't know the answer to all of them, so I'll just answer a few...

1. I think you'll get into a few of these programs for sure.

2. The schools you picked seem fine to me.

3. Assuming they're rigorous courses, I'd assume so. I don't think anyone could answer this question on this forum because no one took the course with you.

5. I think your profile looks very strong for data science / data analytics, assuming the courses you took were rigorous. But if you're interested in that, you should study that and not quant finance.

5.1 Yes. And they are several times more abundant.

7. I would say that your business experience makes you a more unique candidate and if you were able to connect your experience to your current interests in some way in an essay, it could bring a lot of value to your application.