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How does a Master's in Mathematics/Statistics sound for my case?

Tutankhamen

Tutankhamen

Joined
1/2/22
Messages
1
Points
11
Context:

I have a Bachelor's in Electrical Engineering and a Master's in Computer Science. As you would expect, my Bachelor's in EE had a strong applied mathematics component to it, but that was 3-4 years ago. My Master's in CS had little/no math.

Case:

I'm looking to pivot myself toward a quantitative developer role in the near future. Specifically with hedge funds/buy-side firms like Citadel/Two Sigma, Jump Trading etc. Note that I'm not considering quantitative researcher or quantitative trader roles, just purely quantitative developer as I enjoy and want to work with software primarily but in the financial space - i.e. Quantitative Software engineers who implement models in code from QResearchers/Traders in an efficient and optimized manner. Now I'm very well aware that QDs will have to have a decent/strong mathematics background to be able to understand and communicate effectively with QRs and QTs and implement their solutions.

So given my background, do you think a second Master's in Mathematics/Statistics would solidify me for that path or is it just a complete waste of time/money? I could do the Master's in 1 year full-time or 2 years part-time. Or should I take online courses/refreshers?

Applied Mathematics electives:

  • Applied Complex Analysis
  • Asymptotic Methods
  • Bifurcation Theory
  • Classical Dynamics
  • Computational Linear Algebra
  • Computational Partial Differential Equations
  • Dynamical Systems
  • Dynamics of Games
  • Finite Elements: Numerical Analysis and Implementation
  • Fluid Dynamics I
  • Fluid Dynamics II
  • Function Spaces and Applications
  • Introduction to Partial Differential Equations
  • Markov Processes
  • Mathematical Biology
  • Mathematical Finance
  • Methods for Data Science
  • Numerical Solution of Ordinary Differential Equations
  • Quantum Mechanics I
  • Quantum Mechanics II
  • Random dynamical systems and Ergodic Theory (Seminar Course)
  • Scientific Computation
  • Special Relativity and Electromagnetism
  • Stochastic Differential Equations
  • Tensor Calculus and General Relativity
  • Vortex Dynamics
Statistics:

  • Probability for Statistics
  • Fundamentals of Statistical Inference
  • Applied Statistics
  • Computational Statistics
  • Statistics Research Project
  • Introduction to Statistical Finance
  • Advanced Statistical Finance
  • Stochastic Processes
  • Contemporary Statistical Theory
  • Bayesian Methods
  • Multivariate Analysis
  • Machine Learning
  • Biomedical Statistics
  • Statistical Genetics and Bioinformatics
  • Big Data
  • Advanced Simulation Methods
  • Data Science
  • Deep Learning with TensorFlow
  • Nonparametric Statistics
  • Time Series Analysis
  • Survival Models
 
Last edited:
I don’t understand the last part of your question. There’s no way you took all of these courses in your EE undergrad, or CS grad. Is that a list of courses of the prospective program you’re looking at?

As a general rule of thumb, and commensurate with your examples, my recommendation to you would be to stick to applied mathematics (PDEs, numerical analysis) and statistics — NOT pure mathematics. So if you were to do a second masters, perhaps try mixing the two — if it’s a masters in statistics, make sure to take a good two semester sequence in numerical analysis. If it’s a masters in applied math, make sure to take a two semester sequence in statistics (I would even do at least 4 higher level classes in stats to really know your stuff. Make sure to do time series analysis. Statistics is very important).

I am somewhat in a similar boat as you; although my masters is in pure mathematics, and I still lack quite a bit of statistics knowledge to feel comfortable on quant interviews, but the tradeoff here is that reading a higher statistics text comes easier because of my background in math (all the linear algebra, analysis arguments in stats are standard).

Now, I can’t advise you on whether to take a part-time vs. full-time masters, or do a second masters at all, since I have no real experience in the field, but my intuition is firing off in all directions that you should probably take that year and do that second masters full-time, and find a professor to do A LOT (>= 3) of projects in an area of quant finance that interests you him, and plaster that all over your resume. If that doesn’t get you offers, nothing will.

Last thing — I am inclined to believe that a full time masters is more valuable than a part time one, because (a) you get it over with sooner and (b) getting a BS job as a monkey programmer and doing a masters on the side (is what I did, although in > 6 years, not 2) funnels you into the monkeys bucket. You get BS work experience at gimmick startup X, and you subsequently start getting the feeling that no recruiter in quant finance takes your resume and experience seriously, and yet it hogs up a fair amount of your resume and talking points, and it's awkward to apply for new grad positions with 2-3 years of work experience (unless, allegedly, your experience is in FAANG). And I don’t blame them. A much stronger case is a new grad with zero experience but good qualifications and a basket of relevant projects to show for it. But again, take all this with a grain of salt. I have no real experience in this field. My two cents.
 
Last edited:
Tutankhamen said:
Context:

I have a Bachelor's in Electrical Engineering and a Master's in Computer Science. As you would expect, my Bachelor's in EE had a strong applied mathematics component to it, but that was 3-4 years ago. My Master's in CS had little/no math.

Case:

I'm looking to pivot myself toward a quantitative developer role in the near future. Specifically with hedge funds/buy-side firms like Citadel/Two Sigma, Jump Trading etc. Note that I'm not considering quantitative researcher or quantitative trader roles, just purely quantitative developer as I enjoy and want to work with software primarily but in the financial space - i.e. Quantitative Software engineers who implement models in code from QResearchers/Traders in an efficient and optimized manner. Now I'm very well aware that QDs will have to have a decent/strong mathematics background to be able to understand and communicate effectively with QRs and QTs and implement their solutions.

So given my background, do you think a second Master's in Mathematics/Statistics would solidify me for that path or is it just a complete waste of time/money? I could do the Master's in 1 year full-time or 2 years part-time. Or should I take online courses/refreshers?

Applied Mathematics electives:

  • Applied Complex Analysis
  • Asymptotic Methods
  • Bifurcation Theory
  • Classical Dynamics
  • Computational Linear Algebra
  • Computational Partial Differential Equations
  • Dynamical Systems
  • Dynamics of Games
  • Finite Elements: Numerical Analysis and Implementation
  • Fluid Dynamics I
  • Fluid Dynamics II
  • Function Spaces and Applications
  • Introduction to Partial Differential Equations
  • Markov Processes
  • Mathematical Biology
  • Mathematical Finance
  • Methods for Data Science
  • Numerical Solution of Ordinary Differential Equations
  • Quantum Mechanics I
  • Quantum Mechanics II
  • Random dynamical systems and Ergodic Theory (Seminar Course)
  • Scientific Computation
  • Special Relativity and Electromagnetism
  • Stochastic Differential Equations
  • Tensor Calculus and General Relativity
  • Vortex Dynamics
Statistics:

  • Probability for Statistics
  • Fundamentals of Statistical Inference
  • Applied Statistics
  • Computational Statistics
  • Statistics Research Project
  • Introduction to Statistical Finance
  • Advanced Statistical Finance
  • Stochastic Processes
  • Contemporary Statistical Theory
  • Bayesian Methods
  • Multivariate Analysis
  • Machine Learning
  • Biomedical Statistics
  • Statistical Genetics and Bioinformatics
  • Big Data
  • Advanced Simulation Methods
  • Data Science
  • Deep Learning with TensorFlow
  • Nonparametric Statistics
  • Time Series Analysis
  • Survival Models
Click to expand...

This is easy: apply for the jobs you want and see if you get any offers. And make sure to chose realistic options as well. Don't decide to go back to school because you inevitably got rejected from the best of the best.

You already have a masters, you probably don't need another. Especially considering your masters is in exactly what you are looking to apply for...

I have never worked as a QSWE, but I am willing to bet it is pretty similar to a SWE. In that case, you do not need an extra degree in math, that is overkill. CS people "know math", but they don't actually "know math." Save yourself the time, money, and qualifications. Applied maths is for quants, and unless you want to be one, I wouldn't bother. Also, ask yourself: If you want to practice CS, do you really think you will like applied math? That is an entirely different ballgame. I did ME in undergrad. I can confidently say that engineering maths to not prepare you for graduate level math taken through the math department.
 
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