Question 1: What programming languages do you know?
Although exceptionally gifted candidates might be hired purely for their maths skills, firms are mainly looking for people who can demonstrate their programming abilities, says Warwick Pearmund, a finance sector consultant at Slate.
Question 2: A car has to run two laps round a large circle with an average overall speed of 60 km/h. If the car completes the first lap with an average speed of 30 km/h, what is the average speed that it has to accomplish in the second lap?
This kind of basic maths question is common in any quant interview, says Razin Ashraf, a consultant at Hays Banking. It’s aimed at not just evaluating your maths ability, but more importantly your ability to think logically and quickly. A speedy response is key but care is needed. “It is easy to fall into the intuition trap and arrive at 90 km/h, which is wrong,” says Ashraf.
Question 3: Walk through the matrix algebra to forecast volatility with multi-systematic equity models.
Pearmund says this is a question for high-frequency desk quants. “It’s designed to sort the wheat from the chaff, and weed out the people who don’t know their stuff,” he says. And it’s not really the kind of question you can cram for before the interview – you either know your stuff, or you don’t.
Question 4: How much time do you spend building databases and cleaning data for analysis?
Here’s another one for the high-frequency quants, though not every interviewer will ask it. Those that do are trying to separate the most serious and dedicated candidates from the rest. “This is the dirty work of the business – not the glamorous stuff – and it can be an opportunity to show how serious you are about the quality of the data you use. It allows you to show how committed you are to every step of the job,” says Pearmund.
Ashraf says it’s important to remember the focus of an interviewer’s questioning will naturally change with specific quant roles.
“If a quant is looking for a role on the cash side/algo side, the questions will be focused heavily on statistics-based questions. Whereas, if it’s a derivative quant, they will be focused on financial math and probabilities,” he adds. A lot of the other interview questions will be related to artificial intelligence/machine learning.