Hi, thank you for the posts and input.
I agree with Liam, technical adaptation/retooling is required to make an effective transition into any new industry since sound financial engineering design and implementation requires a team effort among finance, math, statistics and information science.
Jose, your question is well taken. My formal degree is in applied math, including phd level probability theory, graduate training just shy of an MS in statistics, 2 years industry experience in software development using C++ with university computer science training in computational modeling, algorithm design, numerical analysis using C++, MatLab, Java, R and SAS.
The university I attended had strong public health and medical school ties with the math/stats/cs department, not finance. This created a practical, time-effective pathway out of academics into a solid industry while concurrently working on a phd in partial differential equations. Bottom-line is that it is difficult to predict how well one fits into a career before gaining hands on experience. And yes, the 'grass is greener' is not to be taken lightly and following a practical career passion tends to increase the quality of life.
Finance is a dynamic industry. Globalization, in conjunction with the massive growth of information technologies, lending itself to new fields like high frequency and algorithmic trading, has increased the financial problem space tremendously. Speaking as someone trained in applied mathematics, statistics and information science, this is exciting.
I am curious if this newer regulatory involvement will prompt positive changes on financial engineering systems by requiring more serious quality control and statistical model validation as employed by medical regulatory agencies? I am curious why many top quantitative finance departments have very close ties with departments of statistics, applied math and computer science?
One reason for my post was to get a sense of whether doing the required independent study, including developing a financial software portfolio, guided by targeted study from QuantNet's master reading list, will be marketable enough? Or will a few good graduate online courses be required in order to pass the initial HR resume screen?