- Joined
- 7/19/25
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I am 44 and I am full professor of physics. I know I am a bit of an unusual case, but I wondering if it possible for someone at my age with my background to transition to quant researcher? If so does it have to be at the same entry level as graduate students? I feel I have more proven skills and more to offer from my experience, but I don’t know how that will be viewed by the people hiring. For more details:
I work in a Chinese University that is only ranked in top 500 or top 1000 in global University rankings. However my undergrad, PhD and previous positions were at places in top 50 or top 100 universities globally.
I have made significant contributions to science and I am quite well known in my field, but I have decided I want to find new challenges and do something different now outside of academia. I got very interested in markets and how they behave while handling my own investments and after spending some time understanding different quant roles I think quantitative research is something I am really well suited for and would find really interesting and fun to do.
Regarding relevant skill sets these are listed below, though maybe a bit tl;dr.
* I am an expert in C++, Python programming (as well as in Mathematica and knowledge of a few other languages). I am an author of many public software packages. I lead teams of researchers to create some of these. Although I still code directly myself in all the codes I work on, in many cases I am supervising students and postdocs who do significantly more of the coding, not sure how that will look to people in finance.
* I handle large data sets (multi TBs in size) and apply Bayesian and frequentist statistics to interpret what the data tells us.
* I perform complex calculations using fairly high level maths and produce precision predictions where careful treatment and attention to detail is essential.
* I use physical intuition to develop hypotheses, and then test them against data to see if they are viable explanations of what we have observed, with physical intuition being one of my strengths.
* I think the above is similar to what quants need when developing ideas and testing them against data. I think really the intuition needed for the ideas is the same skill in both cases, it’s about having a simpler picture in your head of the maths / how things work that allows you to quickly imagine possible mechanisms that work and see the direction they are likely to go in, how they might explain interesting features in the data etc. Then you can work through the calculation in detail and test it, and if it works out you can extend it into a proper model and test that too.
* I am a very experienced and capable communicator, explaining complex ideas to many different levels of audience: world experts, students, grant agencies, the general public and journalists. I think being able to explain the models in simple terms to e.g. traders who will use them is also an important skill for a quant researcher.
* I have some experience and knowledge of AI / machine learning, though it is a bit shallow currently (this may change soon).
I work in a Chinese University that is only ranked in top 500 or top 1000 in global University rankings. However my undergrad, PhD and previous positions were at places in top 50 or top 100 universities globally.
I have made significant contributions to science and I am quite well known in my field, but I have decided I want to find new challenges and do something different now outside of academia. I got very interested in markets and how they behave while handling my own investments and after spending some time understanding different quant roles I think quantitative research is something I am really well suited for and would find really interesting and fun to do.
Regarding relevant skill sets these are listed below, though maybe a bit tl;dr.
* I am an expert in C++, Python programming (as well as in Mathematica and knowledge of a few other languages). I am an author of many public software packages. I lead teams of researchers to create some of these. Although I still code directly myself in all the codes I work on, in many cases I am supervising students and postdocs who do significantly more of the coding, not sure how that will look to people in finance.
* I handle large data sets (multi TBs in size) and apply Bayesian and frequentist statistics to interpret what the data tells us.
* I perform complex calculations using fairly high level maths and produce precision predictions where careful treatment and attention to detail is essential.
* I use physical intuition to develop hypotheses, and then test them against data to see if they are viable explanations of what we have observed, with physical intuition being one of my strengths.
* I think the above is similar to what quants need when developing ideas and testing them against data. I think really the intuition needed for the ideas is the same skill in both cases, it’s about having a simpler picture in your head of the maths / how things work that allows you to quickly imagine possible mechanisms that work and see the direction they are likely to go in, how they might explain interesting features in the data etc. Then you can work through the calculation in detail and test it, and if it works out you can extend it into a proper model and test that too.
* I am a very experienced and capable communicator, explaining complex ideas to many different levels of audience: world experts, students, grant agencies, the general public and journalists. I think being able to explain the models in simple terms to e.g. traders who will use them is also an important skill for a quant researcher.
* I have some experience and knowledge of AI / machine learning, though it is a bit shallow currently (this may change soon).
