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How can I improve my admissions profile and which year should I apply?

Joined
11/27/22
Messages
4
Points
3
Education:
Graduated from Bowdoin College in 2021 with a double major in math and economics. 4.0 GPA.
Relevant coursework, listing the official names that would be seen on my transcript and in some cases providing context:
  • Intro to Analysis
  • Advanced Analysis (measure theory and stochastic calculus)
  • Linear Algebra
  • Intermediate Linear Algebra (applications like PCA and PageRank)
  • Probability
  • Statistics (calculus-based)
  • Advanced Topics in Probability and Stats (bayesian stats)
  • Econometrics
  • Calc I, II, III
  • Intro to Computer Science
Other courses in math that are less applicable:
  • Combinatorics and Graph Theory
  • Rings and Fields
  • Advanced Topics in Rings (algebraic geometry)
  • Advanced Topics in Geometry (non-euclidean geometry)
  • Number Theory and Cryptography
Work Experience:
  • Fall 2022-Present: software engineer at a mid-size startup. Some work in ML but most of it is standard full-stack. Almost exclusively python and typescript.
  • Summer 2021-Fall 2022: construction job/gap year
  • Summer 2020: economic consulting internship. Just data analysis in R and excel
  • Summer 2019: UConn Markov Chains REU. Worked on a paper for nonlinear random walks and presented findings at a conference at UMass. Coding in python.
Perceived Weaknesses:
  • Bowdoin is a small liberal arts school, so despite its high ranking within that category (#6 nationally), I am not sure if it counts for much
  • I don't have any courses in finance on my transcript, my economics courses were strictly economics
  • I took a year off after I finished undergrad to work a job in construction and figure out what I wanted to do in life. It feels like a lot of people in the quant world haven't meandered as much as I did
  • I don't have any courses explicitly in C++ or differential equations. I have worked with both but don't really have much to show for it...
Questions:
  1. Do I have time to get ready to apply for enrollment in 2024? - ie. I still need to study for and take the GRE, I also should brush up on my math skills
  2. Should I demonstrate interest in becoming a quant by taking the Pre MFE courses from CUNY Baruch? I just missed their start dates, and it seems I may have to wait until October to try taking them again? By that point is it a bit too late to get ready for 2024 enrollment applications?
  3. Should I wait to apply for enrollment in 2025? Will I be "too old" then? From the profiles I've been able to stalk on LinkedIn, it seems like a lot of people enter these programs immediately after undergrad
  4. What schools seem realistic? CUNY Baruch and CMU are my top choices but they are also the top choice for many people. Which schools seem like they could be a good fit?
 
You should have a good shot at Baruch. I've met several students like your profile in the programs. They did well and got a good career in finance. Sometimes, those with untraditional background would stand out and make the best of the MFE degree.
I think you should take the QuantNet C++ courses to strengthen your application. There is an Options course here that will help a great deal since you will be asked those options theory during your MFE admission and internship interviews rather soon.
 
You should have a good shot at Baruch. I've met several students like your profile in the programs. They did well and got a good career in finance. Sometimes, those with untraditional background would stand out and make the best of the MFE degree.
I think you should take the QuantNet C++ courses to strengthen your application. There is an Options course here that will help a great deal since you will be asked those options theory during your MFE admission and internship interviews rather soon.
I appreciate the vote of confidence and the advice -- will certainly look into the C++ and Options courses! Also how would you recommend I review my math? I saw that CUNY Baruch does their own QBA test and looked at the topics. Are there any good resources for practice problems or would ones I create on my own from my old notes and textbooks be sufficient?
 
Connor,
I'd love to see how you go through this journey as this reminds me of what I've gone through almost 20 years ago. There were up and down but it's good to have companies along the way and I'm sure you will find plenty of future classmates or colleagues here.
 
Connor,
I'd love to see how you go through this journey as this reminds me of what I've gone through almost 20 years ago. There were up and down but it's good to have companies along the way and I'm sure you will find plenty of future classmates or colleagues here.
I appreciate you saying that. I felt a little behind the curve after taking a year off but I also logically know that it doesn't matter much in the long run. Hearing stuff like this helps that lesson sink in!
 
I'm sure you will find plenty of future classmates or colleagues here.
What would be nice is some sort of group where people take on projects together, or perhaps Kaggle competitions, or anything else that is relevant. I think the strength of the Quantnet community is not utilized to its fullest potential. Lots of thinking required around how to do so, but it's something I would be interested in.
@Andy Nguyen
 
I appreciate you saying that. I felt a little behind the curve after taking a year off but I also logically know that it doesn't matter much in the long run. Hearing stuff like this helps that lesson sink in!
When I did my MFE in 2006, lot of my classmates were in their 30s and having different career/background (law/medical/sales/etc) and we all paid our dues going through the grueling process of the MFE. This should give you in some perspective. There are always younger, better candidates but the successful ones I know are those who persevere.
 
What would be nice is some sort of group where people take on projects together, or perhaps Kaggle competitions, or anything else that is relevant. I think the strength of the Quantnet community is not utilized to its fullest potential. Lots of thinking required around how to do so, but it's something I would be interested in.
@Andy Nguyen
100% agree. I think we have lot of lurkers here and there are lot to be gained collectively if people take initiative and be more open to connect.
I'm happy to discuss and work on any idea or initiative you have.
 
Hey @connorwfitch,
Your personal timeline will affect best time for application but here are some pointers on how to prepare for your transition into this field.

Brush up on mathematics and programming skills: Financial Engineering requires a strong foundation in mathematics and computer programming. Reacquainting yourself with linear algebra, calculus, statistics, and programming languages like C++ Python will be beneficial. QuantNet has several popular online courses taken by thousands of MFE applicants over the years. Lot of MFE programs know about the courses so it's known asset.

Read up on financial concepts: The MFE program deals with financial concepts like derivatives, fixed income, risk management, and quantitative trading. Familiarizing yourself with these concepts will give you a better understanding of what you will be studying in the program. There are plenty of books you can get to get yourself familiar with the topics.

Get experience with data analysis: Financial engineering involves a lot of data analysis and modeling. Familiarize yourself with data analysis tools and techniques such as Excel, SQL, and machine learning algorithms.

Network with professionals: Building a network of professionals in the financial industry can help you learn more about financial engineering and prepare you for the program. Attending events and joining online communities are great ways to start building your network.

Prepare a strong application: The admissions process is highly competitive. Make sure your application is well-written, demonstrating your skills and experiences related to financial engineering. Highlighting your relevant work experience, internships, and academic achievements will be beneficial.

Study for the GRE: Many MFE programs require the GRE for admission. Start preparing for the GRE early and take practice tests to assess your strengths and weaknesses. Some MFE programs now move away from requiring GRE and to administer their own tests.

Apply to several programs: Applying to multiple programs increases your chances of getting accepted into a MFE program. It also gives you the opportunity to compare different programs and choose the one that best suits your goals.
 
What would be nice is some sort of group where people take on projects together, or perhaps Kaggle competitions, or anything else that is relevant. I think the strength of the Quantnet community is not utilized to its fullest potential. Lots of thinking required around how to do so, but it's something I would be interested in.
@Andy Nguyen
I would love this. I only know one other at my university who is interested in quant fin but he is going for the software engineering side. We have talked about finding a project but don't know where to start. Also, data sets are not just lying around, excepting kaggle.

But until he is willing to get any stats skills to complement his coding, two manning a kaggle competition doesn't seem the best use of our time, so we stick with course work and outside reading hoping to find an idea. Well, I do outside reading, he does coding.

Any update on this after the exam? (Hope that went well btw).
 
I don't see how you would have any issues getting into a top program. You've demonstrated a lot of potential and took a strong selection of courses. I guess you just need to write a convincing PS and get 90th percentile+ GRE scores or close to 90th.
 
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