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.[prbreak][/prbreak]
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:
Personality and Communication Skills
Believe it or not, you are not quite as unique as you might think you are. Everybody in this field is “smart”. The ones who get jobs—and then progress upwards through the ranks—have one commonality: people (at least someone) like them. You need to be articulate and outgoing. Inquisitive, yet thoughtful. One way to help your personality show through would be to join Toastmasters or a similar organization. While you may not ever be in sales or a refined public speaker, it will only serve to help differentiate yourself from being like everyone else.
Probably the most overlooked need beyond the technical skills required in this field is the need for communication, Specifically, communication in the English language. English is the universal language of finance—the same as if you were an international airline pilot. If you are not a native speaker, it would be extremely helpful to take communications courses to help with your grammar, presentation, and writing abilities. Even if this is not part of your curriculum, outside tutoring would not hurt you. After all, you may be the smartest mathematician in the world, but if you can’t articulate it so that people understand you, or if your writing skills are so atrocious (author included here . . . ) that it is impossible to follow in a linear fashion, you’re severely disadvantaged.
Programming
If you’re not good at it, get good at it. In almost every role in quantitative finance you will be required to program. The better you are, the easier it will be for you to land a job in the field. Languages to concentrate on are: C++, Perl, Python, Java, C# / .NET, Scala, Hadoop, MATLAB (not a substitute for C++!) and other functional programming languages.
Economics and Finance
In the world of quantitative trading, economics and finance classes are not important—other than for being a well-rounded professional at a macro level. Within the world of quantitative strategists, there is a chasm. Most banks and hedge funds look for those who have a rigorous math background. However, there are a number of hedge funds and asset managers who look to avoid those backgrounds. They want classically trained economists with PhDs from the major Ivy League schools. If you don’t have a PhD from one of those schools and a top undergrad from the same level institution—don’t waste your time. This field is fiercely competitive and you need to up your game to even have an opportunity to interview.
Math
There are a lot of different areas within math, but there is one thing for certain: if you’re going to be a derivatives quant, you had best be good at stochastic calculus. Other areas of note are linear algebra, spatial geometry, and familiarity with partial differential equations and ordinary differential equations.
Internships
The ability to secure an internship should be a priority from the moment you walk in the door as a freshman in college. You get to learn about what these people do on a daily basis, and you may have an opportunity for a rotation. You get to be on the Human Resource department’s radar—a big thing once you are ready to enter the job market. The best way to find a job is to have one in hand as you get ready to graduate because you’ve interned at the company and they feel they need to have you on their team because you impressed them so greatly as an intern. Most importantly, you begin to network with other professionals in the field. People move often and it is 99.99% likely that you will leave your first job within five years. The saying “It’s not what you know, it’s who you know,” carries a lot of weight in the hiring world. Get to know as many people as you can and actively engage with your network often.
Continuing Education
If there were ever a time to recommend staying the distance if you have your sights on a PhD, now is the time. Entering the market later with a PhD may put you at the top of the candidate list, as well as position you to job search in a better market. Not interested in a PhD? Not a problem. There are many different quantitative networking groups, conferences, and symposiums in every financial center to keep you engaged in the latest trends and ideas, and also—and I cannot stress the importance of this enough—the ability to network not only with your peers, but the level of successful professional that you all strive to be.
One other thing that you need to do is read. Voraciously. I’m not speaking about books, articles, and literature dedicated to your field of endeavor. I’m speaking of information flow that is real-time and/or relevant to recent events. If you don’t know what is going on around you, it is hard to have an opinion about what is going on around you. Read The Wall Street Journal, Financial Times, and other newspapers. Subscribe to e-zines such as Fierce Finance or FINAlternatives. Join specific web communities such as QuantNet, Wilmott, or Nuclear Phynance. Read books by Michael Lewis or other topical books relevant to finance (I’m personally a huge fan of Roger Lowenstein’s When Genius Failed: The Rise and Fall of Long-Term Capital Management). Become a well-rounded quant and you will start to move away from the pack.
The purpose of this article is to give you a general overview of the market, the trends, and what skills I believe you should have based upon what positive and negative stresses I see in the market now and in the next few years. Ultimately, I hope that you remember the ultimate lesson here: each of your own situations and experiences is unique to you. Clarity of your path is the most important thing to you. Keep the goal in mind as you make your decisions and, with a bit of luck and good timing, you will arrive at the point you’re aiming for.
****** I need to add a caveat to the article: please keep in mind that given the nature of the function I serve is to be able to 'find a signal in the noise', I receive hundreds of resumes and I can only devote so much time to each. That being the case, the above serves as a very generic, broad-based assessment. Further, our clients pay for us to find them talent that is already in the work force and are currently in a role that they need to fill. I never work with entry-level candidates as none of our clients utilize us for these roles. That said, I am always willing to offer the best advice I can, but please understand that each individual, each role and each company is unique and all of the above or none of the above may apply. ******
This article is featured in the QuantNet International Guide to Financial Engineering Programs.
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.[prbreak][/prbreak]
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:
Personality and Communication Skills
Believe it or not, you are not quite as unique as you might think you are. Everybody in this field is “smart”. The ones who get jobs—and then progress upwards through the ranks—have one commonality: people (at least someone) like them. You need to be articulate and outgoing. Inquisitive, yet thoughtful. One way to help your personality show through would be to join Toastmasters or a similar organization. While you may not ever be in sales or a refined public speaker, it will only serve to help differentiate yourself from being like everyone else.
Probably the most overlooked need beyond the technical skills required in this field is the need for communication, Specifically, communication in the English language. English is the universal language of finance—the same as if you were an international airline pilot. If you are not a native speaker, it would be extremely helpful to take communications courses to help with your grammar, presentation, and writing abilities. Even if this is not part of your curriculum, outside tutoring would not hurt you. After all, you may be the smartest mathematician in the world, but if you can’t articulate it so that people understand you, or if your writing skills are so atrocious (author included here . . . ) that it is impossible to follow in a linear fashion, you’re severely disadvantaged.
Programming
If you’re not good at it, get good at it. In almost every role in quantitative finance you will be required to program. The better you are, the easier it will be for you to land a job in the field. Languages to concentrate on are: C++, Perl, Python, Java, C# / .NET, Scala, Hadoop, MATLAB (not a substitute for C++!) and other functional programming languages.
Economics and Finance
In the world of quantitative trading, economics and finance classes are not important—other than for being a well-rounded professional at a macro level. Within the world of quantitative strategists, there is a chasm. Most banks and hedge funds look for those who have a rigorous math background. However, there are a number of hedge funds and asset managers who look to avoid those backgrounds. They want classically trained economists with PhDs from the major Ivy League schools. If you don’t have a PhD from one of those schools and a top undergrad from the same level institution—don’t waste your time. This field is fiercely competitive and you need to up your game to even have an opportunity to interview.
Math
There are a lot of different areas within math, but there is one thing for certain: if you’re going to be a derivatives quant, you had best be good at stochastic calculus. Other areas of note are linear algebra, spatial geometry, and familiarity with partial differential equations and ordinary differential equations.
Internships
The ability to secure an internship should be a priority from the moment you walk in the door as a freshman in college. You get to learn about what these people do on a daily basis, and you may have an opportunity for a rotation. You get to be on the Human Resource department’s radar—a big thing once you are ready to enter the job market. The best way to find a job is to have one in hand as you get ready to graduate because you’ve interned at the company and they feel they need to have you on their team because you impressed them so greatly as an intern. Most importantly, you begin to network with other professionals in the field. People move often and it is 99.99% likely that you will leave your first job within five years. The saying “It’s not what you know, it’s who you know,” carries a lot of weight in the hiring world. Get to know as many people as you can and actively engage with your network often.
Continuing Education
If there were ever a time to recommend staying the distance if you have your sights on a PhD, now is the time. Entering the market later with a PhD may put you at the top of the candidate list, as well as position you to job search in a better market. Not interested in a PhD? Not a problem. There are many different quantitative networking groups, conferences, and symposiums in every financial center to keep you engaged in the latest trends and ideas, and also—and I cannot stress the importance of this enough—the ability to network not only with your peers, but the level of successful professional that you all strive to be.
One other thing that you need to do is read. Voraciously. I’m not speaking about books, articles, and literature dedicated to your field of endeavor. I’m speaking of information flow that is real-time and/or relevant to recent events. If you don’t know what is going on around you, it is hard to have an opinion about what is going on around you. Read The Wall Street Journal, Financial Times, and other newspapers. Subscribe to e-zines such as Fierce Finance or FINAlternatives. Join specific web communities such as QuantNet, Wilmott, or Nuclear Phynance. Read books by Michael Lewis or other topical books relevant to finance (I’m personally a huge fan of Roger Lowenstein’s When Genius Failed: The Rise and Fall of Long-Term Capital Management). Become a well-rounded quant and you will start to move away from the pack.
The purpose of this article is to give you a general overview of the market, the trends, and what skills I believe you should have based upon what positive and negative stresses I see in the market now and in the next few years. Ultimately, I hope that you remember the ultimate lesson here: each of your own situations and experiences is unique to you. Clarity of your path is the most important thing to you. Keep the goal in mind as you make your decisions and, with a bit of luck and good timing, you will arrive at the point you’re aiming for.
****** I need to add a caveat to the article: please keep in mind that given the nature of the function I serve is to be able to 'find a signal in the noise', I receive hundreds of resumes and I can only devote so much time to each. That being the case, the above serves as a very generic, broad-based assessment. Further, our clients pay for us to find them talent that is already in the work force and are currently in a role that they need to fill. I never work with entry-level candidates as none of our clients utilize us for these roles. That said, I am always willing to offer the best advice I can, but please understand that each individual, each role and each company is unique and all of the above or none of the above may apply. ******
Todd Fahey is Executive Director, Global Head – Quantitative Strategies Practice, at Sheffield Haworth, Inc. He has trained quantitative and technical recruiters; published articles, blogs, and e-zines; and presented at various business schools. He can be reached at fahey@sheffieldhaworth.com.
This article is featured in the QuantNet International Guide to Financial Engineering Programs.
