comparative perspectives to professionalism

Here are two answers to a question asking about paths to a career in quantitative finance:


Stand out of the crowd.If you are really looking for a HF quant career, go for a Master in Math or Physics, learn to program in C++ and mastering the Mathematica software.
Get an extra interest in Radioastronomy (wave theory is very related to financial markets), try to go to work with Prof Henry Lo at MIT Finance Lab.
and add some studies in Behavioral finance aimed at building behavioral quant elements in algos.
But don't go for another MBA (there are dozens out there..with experience) and don't bother for a CFA, unless you really have extra free time and don't know how to use it better.
CAIA may be culturally interesting, but still a young quali to have weight...

I am hiring a Civil Engineer with an MBA, yes, but a an extra Master in Math and C++ programming skills. I would have hired him without MBA...but not without the Math and programming skills.

Stand out of the crowd...MBAS are becoming too common to carry weight, at least that's what my colleagues are saying.


[the previous answer] hit it on the head, stand out from the crowd. But I would lean towards a communication approach instead of a “smart-person” approach.

The quant world is chock full of smart people, it feels like every genius with a PhD has already left academia for the siren call of six-figure salaries. When you talk to investment bankers, what they want today are two things; 1) People who can communicate effectively and concisely, and 2) answers - not more models.

Five years ago, hedge funds were trying to ramp up sophistication because there was a lot of easy money chasing “new ideas”. Researchers got to play with wave-form models and random forests to predict market movements. The recent financial crisis made people take a step back and ask some honest questions. First, how does GIGO (garbage in, garbage out) play into these models? Second, what is the value of these unbelievably fancy models? Can we still support or use them when our researcher with a 190 IQ gets poached by a different fund? Are simple to maintain GLM models good enough? Do our models account for rare events, or are they ignoring the Black Swan? How do I explain this stuff to an investor?!

A good approach to take in today’s environment, is a background in effective communication and illustration of how you can get answers for people. Your background is in marketing, so you should have a leg up on communication skills over pure modeling expert. I would start with an MBA from a top 50 (preferably top 15) school, a CFA is a nice add-on, but school quality is worth more. Make sure and focus on math/statistics/finance/programming, you must have these skills, but IMO, they play second-fiddle to communication these days. Focus on networking at school and lead every group project and every presentation. If you can hack that, you’ll be able to sell yourself as a communicative leader that can manage quant-analysts and get answers.

One is hiring, one is European, one is not working in the US; Go figure!