Quantitative analysts develop high-level trading and risk management strategies using complex algorithms and mathematical equations. This is a career for the top 1% in numerical proficiency. If you were always the math whiz in class, even at the post-graduate level, a lucrative career in quantitative analysis could be in your future.
Most quantitative analysts have at least a master's degrees, with many carrying doctorates in fields like mathematics or statistics. Indeed, quants' most common college majors are mathematics, economics and statistics, with strong academic performance paramount for getting a foot in the door.
Assuming you have the credentials to get an interview, you need to shine, because your competition is going to be elite. Anticipating the most likely questions lets you practice delivering winning responses with confidence.
- Quantitative analysts, or 'quants', perform the number crunching and statistical analysis for companies in all sectors of the economy.
- Computer skills are a key, and you should know your way around several of the popular and current programming languages.
- You should also know how to build and evaluate statistical models as well as have a good handle on your math skills.
- In a job interview, be prepared to be quizzed on your background and qualifications in each of these domains.
Computer Skills and Programming Languages
Apart from math skills, computer skills are the next most important thing to have as a quantitative analyst. Trading operations, in particular, need quantitative analysts who can program complex algorithms into their trading software. Algorithm-based computerized trading, in particular high-frequency trading (HFT), in which securities are bought and sold electronically at a frenetic pace, has replaced much of the manual trading on Wall Street. The firms with the fastest, most effective algorithms reap the most profits.
As of 2022, the most valuable computer language to have mastered is Python. However, expertise in SQL, Java, C++, and even advanced Excel can add value, so highlight all of the computer knowledge you possess.
The interviewer wants to see that you have applied your knowledge not only in theory but in practice. He also wants to assess your models themselves and determine whether your thought process aligns with what the company is looking for. Even if you have a different trading philosophy than your interviewer, this is not always a bad thing, particularly if you can demonstrate where your models have enjoyed a track record of producing big gains.
When you get this question, the most important thing is how clearly and confidently you explain your past accomplishments. A bit of salesmanship goes a long way. Before your interview, prepare by making a list of your biggest modeling and forecasting accomplishments, and then practice describing them to an interviewer.
Mastery of statistical software packages like Stata, SPSS, and/or R will be helpful.
At some point during the interview, you are going to feel like you are back in school. Expect an impromptu math question. The interviewer wants to see you employ your high-level quantitative skills to reason through it as quickly as possible. They might ask you a probability question about a stock trade, or possibly a variation of the old handshake riddle: How many people are at a party if 100 handshakes take place and everyone shakes hands with everyone else?
The possibilities for questions are almost endless, making it difficult to prepare for anything specific. Get plenty of sleep the night before your interview, and go in focused and ready to think on your feet. Trust that since you qualified to interview for a quantitative analyst position, your math skills are good enough to handle whatever the interviewer might throw your way.
The Bottom Line
Quantitative analyst is a high-level job, so ask high-level questions when the interviewer prompts you. Probe the company's trading philosophy, ask about the technology it employs, and determine what tools you will have at your disposal. Show the interviewer that you mean business and that you want to be equipped to make a difference for your new employer from day one.