Are you considering a quantitative career in finance? You’re in high demand as specialties like quantitative trading and portfolio and risk management come of age.
A job as a quant analyst requires a high level of motivation and commitment, but the rewards far outweigh the effort. You have the opportunity to work in a modern, fast-paced environment surrounded by some of the smartest people on the planet. And on top of it, you’re handsomely compensated for your work.
The basics include mastering both theory and practical implementation, with knowledge and skills in areas including probability, statistics, stochastic calculus, options/derivatives and C++, Python, MATLAB or R.
Are You an Undergrad?
If you’re an undergraduate studying math, physics, engineering or computer science, you’re on the right track. Investment banks and hedge funds have an interest in recruiting top students. You can steer your career path in a number of directions including:
- Probability: This is the most fundamental aspect of quant finance. An understanding of probabilistic concepts is essential if you want to work effectively – or even work at all – in the field.
- Stochastic calculus: This is the toolset through which a quant expert manipulates the Black-Scholes model for derivatives pricing. You need this background if you want to price options.
- Statistics: If you want to go directly into quant trading, you’ll need a sophisticated level of statistical background and intuition. Take as many stats courses as possible.
- Programming: As a quant analyst, you’ll spend a significant percentage of your time implementing models. If you work at a bank, you’ll probably use C++/Java C#. At a fund, the options may range from C++ or R to MATLAB or Python. If you excel at programming, you position yourself at the top of the job candidate list.
If you launch your career after earning your undergraduate degree, you can enter a bank as an entry-level analyst or, if you’ve majored in technology, in a quantitative developer role.
You may want to consider an internship at a bank or hedge fund. The latter are harder to get, since funds generally limit their intern selections to those from the world’s top schools. But it will give you an added degree of prestige, which is a competitive advantage in the world of finance.
Individuals working on a math doctoral program have a wealth of opportunities to implement models in any language. Depending on your specific field, you’ll use C/C++, Python, MATLAB or R – and these are exactly what you’ll need to jump start your quant analyst career.
Keep in mind that academic programming differs from another key area of quant analysis: software development. The latter is not often emphasized while implementing academic models. To stay ahead of the game, be sure to learn some professional coding techniques.
A word of caution on MS degrees in financial engineering: There currently is an oversupply of talent in this area, as the market has contracted in the past five years. You can no longer assume that this degree will land you a quant analyst position particularly for those whose undergraduate degree is in engineering or technology. In that case it’s much more likely you’ll be offered a role that will follow a quantitative developer path.
Contact a specialized recruiter as you near the end of your academic program. Working with a quant analyst career coach at a firm specializing in your area is an excellent strategic move. Their industry knowledge, professional contacts and expertise are invaluable in finding the perfect position to fast-track your career. To learn more, read our related posts or contact Select Group, Inc., today.