I'm a developer with very little statistics knowledge who at one time had extensive math knowledge, but haven't applied it in so long that I don't recall most of it these days.
I worked in the finance sector as a (lead) developer on a production use trading system for quite some years. None of the developers had formal math or statistics knowledge to the extent required to develop this system.
This didn't really bother anyone in the least despite the fact a mistake could cause a loss of millions of dollars in practically no time at all...
The reason for this wasn't because anyone was ignorant enough to think the programmers knew what was going on. It was because it was a finance company that also employed plenty of mathematicians, statisticians, physicists, and other's with the proper math/stats background. The programmers wrote the code, but the math/stats people wrote the business rules and the formulas and extensively tested that the system worked correctly against a large enough variety of models with expected outcomes that they were able to have sufficient confidence that the system reward/risk measurements were appropriate.
So my answer would be no; I don't find this all that troublesome. We can't be experts at everything and smart companies realize this so they should be creating teams with the correct skillset to be successful.
I worked in the finance sector as a (lead) developer on a production use trading system for quite some years. None of the developers had formal math or statistics knowledge to the extent required to develop this system.
This didn't really bother anyone in the least despite the fact a mistake could cause a loss of millions of dollars in practically no time at all...
The reason for this wasn't because anyone was ignorant enough to think the programmers knew what was going on. It was because it was a finance company that also employed plenty of mathematicians, statisticians, physicists, and other's with the proper math/stats background. The programmers wrote the code, but the math/stats people wrote the business rules and the formulas and extensively tested that the system worked correctly against a large enough variety of models with expected outcomes that they were able to have sufficient confidence that the system reward/risk measurements were appropriate.
So my answer would be no; I don't find this all that troublesome. We can't be experts at everything and smart companies realize this so they should be creating teams with the correct skillset to be successful.