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So You Want to Be a Financial Engineer?

Preparing for a Career in the Field - When preparing for a career in Financial Engineering, it’s helpful to know what you need to know in order to be considered a good candidate for a job, as well as how to be successful in that role once you are hired.

First, you should know that the general utilization of an MFE degree tends to be oriented toward quantitative roles on the desk (i.e., working on the trading desk and delivering the models, risk calculators, etc., directly to the traders who utilize their products), or in risk management, model validation, and library control, CVA, or quantitative development and programming.

I’ve been a recruiter for more than 14 years, and have worked exclusively in quantitative finance for the last 12 years. My coverage spans global investment banks, hedge funds, proprietary trading companies, and asset management firms, focusing on the front-office quant and trading and technology professionals. The vast majority of roles that I cover are automated/systematic/algorithmic quants and traders through quantitative software and systems/platform developers and quantitative analytics and modeling on the desk. I will discuss in more detail how to prepare yourself for these roles, and help you focus on the subjects you need your degree program to teach you.

While the job market is very soft for new MFEs hitting the market to be desk quants, as well as those in exotics and structured finance, there is a significant need within the CVA, risk, and quant developer/programming fields right now. I anticipate this need will only grow stronger over time as there is significant emphasis on risk and credit at the moment—and the foreseeable future—specifically as it relates to the current regulatory environments both here and abroad.

The other area that is bright at the moment is within the world of automated, algorithmic, systematic, and quantitative trading. These roles are highly competitive for entry-level professionals. Further, they all require programming skills in core languages, along with a solid knowledge of statistical, neural network and/or artificial intelligence methods. If this is a route you are looking to pursue, you need to know that you will be facing some ridiculously stiff competition, and you may be best served by being open to relocation outside of the U.S.—Asia in particular. Also, work hard on getting solid skills and experience with C++, Python, Java, and/or Scala, as these tend to be the most utilized programming languages in the field.

My personal recommendation if you’re looking for a job now, in terms of target companies would be, in order: hedge funds, asset management firms, proprietary trading companies and, finally, banks. The reasoning behind this is that banks are in regulatory hell right now; proprietary trading companies could very well have some issues with the pending regulations in the U.S. and the UK, and there is still a lot of money waiting for deployment across the global spectrum right now. Asset management firms and hedge funds appear to be the beneficiaries of what we anticipate over the next 5-10 year stretch.

But how do you prepare for these jobs? First, it’s helpful to know what to prepare for in terms of education, based upon your interests. For example, if you desire to pursue a path in high frequency futures trading, you should be aware that the vast majority of these people do not have PhDs, and some employers in this field actually believe them to be detrimental. A strong background in electrical and/or computer engineering (with a master’s degree, preferably), very strong programming skills (C++, Java, C#, Scala, Python, etc.) and comfort with very large data sets is key. If you are more interested in the mathematical side, a PhD is the preference, although not a necessity (MFEs typically work in this arena, as well). Typical coursework for these careers is Operations Research, Applied Mathematics, Mathematics, Theoretical Physics (not experimental—not a desirable math track), Electrical Engineering, Computer Science or Engineering, and Mechanical Engineering. If you decide that this is the path to pursue, understand that strong programming is a requirement and will be done every day. It is no longer optional. And, if you can only program in MATLAB, SAS, S+ or another RAD or statistical package, you will be at a disadvantage compared with those who can program in advanced languages mentioned above.

What do you need to know to make yourself competitive in the market wherever you choose to work in the world? Let’s face it—this is probably the most competitive field of employment outside of professional sports. As such, talent alone might not get you in the door. There are things that you should do in order to make yourself stand out from the crowd. Including some things that may make you uncomfortable and push you in directions you may not have considered prior to pursuing this career path. I will highlight the things I believe that will best start you on the path to success:

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