The Two Types of Quant Interviewers

Quant Interviews

When interviewing with a prospective quant firm, one will typically undergo a series of interview rounds in which you will be introduced to various quants working at the firm. Since quant firms hire from a diverse pool of talent, each quant may have expertise in their own field of study and the questions they ask during your interview may be reflective of the concepts and topics that they are most familiar with. For example, a quantitative researcher who has spent half a decade studying physics in academia, has a higher likelihood of asking you a question related to the dynamics of stochastic processes than a niche topic within finance such as the binomial pricing model.

In general, there are two broad archetypes of quant interviewers that you will encounter throughout your interviews. These two types are:

1. The Pure Mathematician
2. The Applied Mathematician

Throughout the rest of this article, we will cover details on how these two archetypes differ and the types of questions each one is most likely to ask. It's important to note that in order to leverage the following information, you must first be able to identify which type of quant you are going to be interviewed by. Oftentimes, the name of your interviewer will be shared with you prior to your interview, in which case, you can find information about them with a quick search on LinkedIn. Furthermore, depending on the type of quant firm you are interviewing with, you can gain a sense for the types of quants that work there.

The Pure Mathematician

The pure mathematician quant is one who has advanced knowledge within the field of probability theory and statistics. These quants typically have PhDs in a branch of finance or statistics and will therefore tailor their interview questions to be more theoretical and proof-driven. During the technical interview, you can expect a mixture of programming and statistics questions concerning topics such as:

1. Monte Carlo Methods
2. Black Scholes Model
3. Measure Theory
4. Stochastic Processes
5. Bayesian Methods

The Applied Mathematician

The applied mathematician quant is one who has a background in a field outside of mathematics, finance, or statistics. These quants typically hold degrees in subjects such as physics, industrial engineering, or computer science. An applied quant will typically have more knowledge in numerical analysis and linear programming, and will therefore assess you on such topics. Examples of topics that may arise include:

1. Optimization Methods
2. Differential Equations
3. C++ Programming
4. Finite Difference Methods
5. Machine Learning

Tips to Appease Your Interviewer

While many like to believe that interviews operate on an efficient frontier, this is simply not the case. Human bias is a major factor that influences whether you will move on to the next round, and therefore it is better to take advantage of this fact rather than dismissing it.

One of the primary ways in which you can make this work to your advantage is by researching your interviewer ahead of time. Understand their background, interests, and profile and structure your questions around topics that they will find engaging. For example, if your interviewer was previously conducting research, ask them about a paper they published or how the program they attended shaped their understanding of quantitative finance. Conversely, if your interviewer previously worked at another firm, ask them about that experience and how it contrasts with the work they are doing at their current firm. These types of questions will earn you brownie points with the interviewer, which may help tip the balance in your favor when the firm is choosing who to move forward to the next round.

Closing Remarks

Overall, in this article, we shared that interviewers at quant firms typically fall under two archetypes: the pure mathematician and the applied mathematician. Understanding which archetype aligns most closely with your interviewer will allow you to assess which practice topics are most important to review.

If you enjoyed this article, feel free to check out the other articles on our Quant blog.