Invited Talk – Mathematics for Beginners

This week I had the honour to open the 1st Season of the conference series “Mathematics for Beginners” organised by the REMIM (Mexican Network of Mathematics Institutes) and the SMM (Mexican Mathematics Society). The series aims to promote mathematics by discussing theoretical and applied topics with a general audience, as well as sharing different career options that students can take after finishing their studies in Mathematics.

I gave a brief overview on how to model interest rates, and oil prices from a practitioner point of view. Of course, I also took this opportunity to talk about the amazing opportunities that new mathematicians (and STEM graduates in general) can find in the Financial industry. Some of the points I wanted to stress:

  • The work that Quants do go beyond understanding complex mathematical models. In particular, implementation, and communication are key parts of the work.
  • Theoretical models cannot be used in practice until they are translated into code. This requires programming skills and is important that mathematicians start acquiring them early in their academic career. A good starting point would be learning the basis of a scripting language such as Python, and start working on small projects to develop a more advanced proficiency.
  • Communication skills are essential for the job. Quants rarely work on isolation. The work tend to be highly collaborative and teams are formed by individuals from diverse academic background –which is fantastic for innovation and productivity! Thus, mathematicians should work on becoming good communicators, especially on explaining complex concepts with simple terms for a general audience. This is something that many times we don’t practice –even worse, we become so accustomed to talk only with other mathematicians that we lose the ability to simplify our messages.
  • Working as a Quant offers you a great balance between working on intellectually challenging problems (as my own manager uses to say, we are always learning!) and also learning how to face more pragmatical matters –e.g. adapting your research process to tight deadlines, understanding that higher complexity is not always the right solution, finding the best solution given the resource constrains.

I was very glad to see so much interest on the work that Quants do, and also many students considering it as a career option!

As promised, here are the links that we visited during the talk:

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