I believe your conversation counter party did not mean to say that the theoretical nature of the applied statistical techniques are too advanced for a graduate math/stats/CS level student to master. I venture to assume what he/she meant was that the applied tool sets specifically to financial trading at that specific firm are/were too advanced for someone fresh out of school to learn and apply in a short period of time.
Actually, I believe this to be sometimes true as well, in case this is what he/she meant. First of all, I think the term and stigma attached to "PhD" level kind of work is hopelessly overrated. A PhD program, dissertation, and defense, means nothing else but that the candidate/holder has specialized on a topic and performed studies/reading in order to familiarize him/herself with the topic in order to do work on his/her own that deepens the understanding of the community which applies similar techniques. Having said that, one does not have to undergo such program in order to amass profound knowledge and add value by performing work in a particular area on his/her own. I have seen guys without college degree but an amazing knowledge (or should I say insight) of mass psychology and expertise in market intrinsics achieving promotion after promotion at major trading desks because of their superior return performance.
Trading and also quant research requires a basic/advanced set of tools in order to understand the subject matter. But real success, from my experience, does not correlate with which school or academic program one underwent but highly correlates with an extraordinary passion for the particular job (as with everything in life), constant learning on the job and from others, an insight into how market players think and behave, time spent to study market structure, a healthy risk appetite but above all a deep respect and understanding of the risk-reward relationship.
Such skills and learned knowledge can often be as complex if not more complex than what PhD level students study and expose themselves to in the ivory towers of the world. Those skills and abilities, imho, often are lacking in many students who pursued relatively theoretical work in university. I loved to ask incoming PhD or science grad school students at my previous trading desks on the sell side what strategy ideas they had, what they think may be worthwhile pursuing, research wise. I asked them what ideas they would pitch to me on the spot. Most of the time there was a shocking silence afterwards and I immediately knew that such student hardly at all spent time on applying any of his/her knowledge to financial markets/time series/assets before.
This bridge/gap, imho, is what is much harder to overcome than learning the tool sets required to study and research financial markets. Additionally, many of such candidates lack a commercial way of thinking, they believe they are paid to perform research like the 1960s/1970s Bell lab guys. The life cycle of what works and does not work in finance is much shorter than in other disciplines and that is something that is very hard to teach and punch into a PhD who comes along with a somewhat academic arrogance, thinking he can conquer the world. Personally I have met countless top traders from universities I have hardly ever heard about, while I most never came across (personally) someone with a highly specialized advanced degree from a top school who beat the rest of the pack.
Long story short, I believe that is what your representative may have meant and referred to. Knowing the theoretical tool is one thing, applying them to finance and extracting alpha requires a much vaster knowledge and is an entirely different thing.