Genuine Advice Appreciated for Pre-MFE and Quant Internships

[Aadithyaa B.]

Hello QuantNet Community,

I have just joined QuantNet and am in awe of the exceptional profiles and mentorship I see on this collaborative platform, and I would be extremely grateful if anyone can give me genuine advice on my current position, advice on future steps to accomplish my goals (top MFE and becoming a quant researcher/trader).

My name is Aadithyaa Balasubramanian and I am a rising sophomore at Stony Brook University's Honors College studying Applied Mathematics & Statistics and Economics (double major with a minor in Industrial Engineering). I took multivariable calc, linear algebra, probability and stats (with calc), and discrete math my freshman year and will take many more classes in quant finance, investments, econometrics, differential equations, operations research, time series, data analysis, probability theory, data science, economics, finance, and about 6 computer science courses (2 masters level) in Python, R, SAS, C, C++, Matlab, and looking to learn SQL and Tableau independently. I have around a 3.7 gpa and hope to graudate around the 3.82-3.87 gpa range. I interned at a wealth-mangement/finance/insurance firm in my freshman summer and will most likely intern at the start of my sophomore semester in a commodities trading research and supply chain role (data analysis and operations research heavy). I am looking to gain internship experience in quant trading/research, IB, asset management, and data science roles throughout my undergrad (would love one or two big name companies/firms) and ideally study at a top MFE. I also will write my senior Honors College Thesis on a quant based topic and like to develop my own trading algorithms (very beginner now but look to enhance skills).
*** I also have math competition awards, research awards, and inductions throughout high school

My key questions are (I apologize again if any of these sound stupid as I am new to this):

- How can I land internships in these areas (from big companies or in general)? (I apply to a lot of internships right from the start and network but know I can improve networking approach)
- How valuable are referrals and do they lose value if everyone is looking for them?
- Is my coursework strong for MFE (any suggested changes or fixes)?
- Is my gpa sufficient for the big MFEs and MF programs (MIT, Princeton, Baruch, UChicago, etc)?
- Any overall advice for what to look out for, avoid, do or don't do would also be greatly appreciated

I would love to connect with anyone and am open to business/internship inquiries as well (sorry if this isn't the right place for that).

Thanks for everyone's time, help, and advice! I greatly appreciate it!

 

[MikeTheQuant]

Hi Aadithyaa,

Good to see you here on QN. I came across your post and figured I'd respond even though we've met on Linkedin. From my username, and reading through my post, you'll quickly realize who I am. Just want to respond to your questions and give a few constructive critiques of your resume. This is all advice that I've received from very successful industry professionals as well as many current MFE candidates from top schools, so I'm not just pulling random advice of my own opinion out of my ass.

1. You don't necessarily need to get quant internships in undergrad. They can be finance (sales & trading, risk, IB, WM, AM), data analysis/science, software engineering, actuarial, accounting, or other adjacent fields. Of course, quant internships maximize your ability to get into MFE, but there are very few available to undergrads. To supplement or replace internship experience, you could be a TA or be a research assistant at your uni.
2. Referrals are good. They can help get you interviews, but you have to perform well in the interview to get the job. Having an overall strong resume and cover letter helps get interviews as well.
3. Your coursework is certainly very strong. Some more classes I would recommend for summer or winter semesters that are available at Stony Brook would be AMS 317 (Linear Regression Analysis), AMS 326 (Numerical Analysis), AMS 335 (Game Theory), AMS 380 (Data Mining), AMS 410 (Actuarial Math), AMS 412 (Mathematical Statistics), AMS 322 (Data Sci & ML in Econ). Obviously, you can't fit every one of these in your schedule, so use your discretion when deciding which of these classes to pursue, but I would say AMS 317 and AMS 326 are the most important of these classes. ECO 322 is great as well since Data Science and ML are big buzz words floating around in the quant space atm.
4. Keep your GPA above a 3.7 and you'll be fine. With a 3.8+, your chances of MFE admissions are stellar.
5. Overall advice: build up your network, reach out to industry professionals on LinkedIn, build good relationships/rapports with your professors (you will need recommendation letters for MFE programs).

Resume:
-Firstly, I wouldn't put your address in a resume that's visible to the whole website. It's ok to leave it there when applying for jobs, though. I'd stray away from leaving such personal information like that for security reasons.
-No need to emphasize your junior standing. Just put down your anticipated graduation month/year
-Don't put down coursework that you have not yet taken. The exception I would make is when you're in the summer/winter and you are enrolled in the classes that you write in your relevant coursework section. Also, only put those classes down in your coursework section if you will have the class completed by the time you will begin the position you are applying for. If you have Time Series in your coursework section, your employer will expect you to be a time series subject matter expert when you begin your desired position. Also be prepared to answer technical questions about Probability Theory, Operations Research, Quantitative Finance, etc. in the interview if they're in your coursework section. I think you get the gist.
-For work & leadership experience, try to split your bullets up into 3 smaller bullet points rather than 1 or 2 large bullet points. It flows smoother and it is more visually appealing. You can ask ChatGPT for help in this area.
-For the other section, it has good content, but it is quite bulky. When you obtain more work/leadership experience (and you will, given your strong background), you will need more space to write about these experiences.

Hope this helps.

 

[Aadithyaa B.]

Hi Aadithyaa,

Good to see you here on QN. I came across your post and figured I'd respond even though we've met on Linkedin. From my username, and reading through my post, you'll quickly realize who I am. Just want to respond to your questions and give a few constructive critiques of your resume. This is all advice that I've received from very successful industry professionals as well as many current MFE candidates from top schools, so I'm not just pulling random advice of my own opinion out of my ass.

1. You don't necessarily need to get quant internships in undergrad. They can be finance (sales & trading, risk, IB, WM, AM), data analysis/science, software engineering, actuarial, accounting, or other adjacent fields. Of course, quant internships maximize your ability to get into MFE, but there are very few available to undergrads. To supplement or replace internship experience, you could be a TA or be a research assistant at your uni.
2. Referrals are good. They can help get you interviews, but you have to perform well in the interview to get the job. Having an overall strong resume and cover letter helps get interviews as well.
3. Your coursework is certainly very strong. Some more classes I would recommend for summer or winter semesters that are available at Stony Brook would be AMS 317 (Linear Regression Analysis), AMS 326 (Numerical Analysis), AMS 335 (Game Theory), AMS 380 (Data Mining), AMS 410 (Actuarial Math), AMS 412 (Mathematical Statistics), AMS 322 (Data Sci & ML in Econ). Obviously, you can't fit every one of these in your schedule, so use your discretion when deciding which of these classes to pursue, but I would say AMS 317 and AMS 326 are the most important of these classes. ECO 322 is great as well since Data Science and ML are big buzz words floating around in the quant space atm.
4. Keep your GPA above a 3.7 and you'll be fine. With a 3.8+, your chances of MFE admissions are stellar.
5. Overall advice: build up your network, reach out to industry professionals on LinkedIn, build good relationships/rapports with your professors (you will need recommendation letters for MFE programs).

Resume:
-Firstly, I wouldn't put your address in a resume that's visible to the whole website. It's ok to leave it there when applying for jobs, though. I'd stray away from leaving such personal information like that for security reasons.
-No need to emphasize your junior standing. Just put down your anticipated graduation month/year
-Don't put down coursework that you have not yet taken. The exception I would make is when you're in the summer/winter and you are enrolled in the classes that you write in your relevant coursework section. Also, only put those classes down in your coursework section if you will have the class completed by the time you will begin the position you are applying for. If you have Time Series in your coursework section, your employer will expect you to be a time series subject matter expert when you begin your desired position. Also be prepared to answer technical questions about Probability Theory, Operations Research, Quantitative Finance, etc. in the interview if they're in your coursework section. I think you get the gist.
-For work & leadership experience, try to split your bullets up into 3 smaller bullet points rather than 1 or 2 large bullet points. It flows smoother and it is more visually appealing. You can ask ChatGPT for help in this area.
-For the other section, it has good content, but it is quite bulky. When you obtain more work/leadership experience (and you will, given your strong background), you will need more space to write about these experiences.

Hope this helps.

Thank you for this amazing detailed insight I greatly appreciate it!