October 4th, 2015, 10:52 am
Well this is an odd one, haven't seen anyone going through the same situation on this forum so I'd like to hear professional's take on the following matter.After several weeks shaping my research proposal together with my potential supervisor, I am now about to submit my application to study a PhD in Mathematics at a Scottish university. Ever since I finished my Masters in Financial Mathematics last year, I have been convinced that studying probability theory is something I would really enjoy doing. However, I have just turned 30, which means that when I finish my PhD I'll be 34 (give or take).I'll sum up my background shortly: I have almost 3 years experience working as software engineer at an investment bank, and after finishing financial maths I have joined a financial engineering team at a rating's agency in London, where my daily tasks involve linear pricing (boring) from time to time and no interesting programming whatsoever since we use an in-house scripting language. I definitely don't enjoy what I do and I'd rather have a much more analytical job related to math finance (Monte Carlo, finite differences, alternative copula function research). I do get interviews at big firms from time to time, but either I end up bombing them or my recruiter gets back to me saying the team really liked me but there is another candidate with a Phd who gets the job. This has been happening for a while already, which is at times frustrating.And here go the two questions, which might seem unrelated but they are really not:1. Is 34 an age which employers might consider a bit too high to access highly quantitative positions? 2. Should I just forget about the PhD and simply keep interviewing until I get a quant job, hating what I do in the meanwhile?I hazard many of you will say "you don't need to do a PhD to be a quant", but I'd like to point out that if I ever start a PhD it would not be exclusively for professional reasons and rather because I want to know more maths and be more able in the future to cope with complex modeling problems at work.
Last edited by
mekornilol on October 3rd, 2015, 10:00 pm, edited 1 time in total.