Graduate / Career change from Finance to Bioinformatics - MS SoP review [2]

Hi guys, I am a foreigner and I was granted permanent residency to the US last January. I can finally afford to go back to school and regain control over my career.

Background: I was VERY successful in my home country, with an undergrad in mathematics and a graduate certificate in finance, employed by a large bank, the first woman and youngest person in my role.

I moved to the US with my husband whos a scientist and got a position here. I had a sequence of setbacks, USPS lost my work permit and I spiraled into financial distress. 4 years later and I'm totally not back on my feet, not even close to where I was. I worked during many years as a CS rep and only recently landed a job in the finance industry.

Now I'm sick and tired of it, I want a refresher, I want to change. But it is SO DIFFICULT to justify this leap, from finances to bioinformatics.

So, help me out to see if my SoP idea is adequate, trying to create a link between my background and new interests, or if I should just start over and write exclusively about doing research without the finance portion.

Thanks a lot.

My vision - Statement of purpose

Research is in the business of innovation and must be conducted as such; paradoxically, basic research is chronically and severely underfunded, and rare diseases are obscured, with only approximately 670 drugs approved since 1983 (there are over 6500 rare diseases, affecting an estimate of 30 million Americans). Financial sourcing and politics still drive the scientific agenda. As a finance graduate, I got it; as a person with a rare genetic disease, I find it outrageous. We got it backward: a sustainable research model must allow science to drive financing decisions and must reduce government participation in its funding. Basic research is about innovation and needs the efficiency of private funding, while deserves autonomy from public or stakeholder opinions. That is what I want to accomplish: I found a bigger purpose in bringing science and business together, to transform the genetic research for rare diseases scenario by improving its fundraising strategy on a large scale, through the slate financing approach.

I am the first in my family to earn an undergraduate degree, and science seemed distant, even mystic to me. It is not anymore; I married a neuroscientist (whom I have been helping in analyzing research data forever). The first-hand experience, in my everyday life with a researcher, made me develop a vision: I envision a future for basic research with better fundraising strategies, fewer barriers for knowledge sharing, and centralized and shared information resources. To integrate finance and biotechnology and solve the funding bottleneck, I need additional, formal, and very specific training in genetics and bioinformatics tools. Computational biology will play an important role in the creation of an extensive biomedical research portfolio, where data is centralized and shared, while research projects fate are independent from public opinion and stakeholder pressures. Bioinformatics can greatly increase basic and translational research success rates by providing modeling of metabolic and genetic processes before any more benchwork is performed and predicting clinical trials outcomes, considerably reducing research costs, and improving its efficiency.

I possess a strong mathematical background, several transferable skills in programming and data analysis, knowledge of business and finance, and I have been in touch with the academic world and basic research for many years. I am eager to participate in the design of basic research's forthcoming paradigm and especially in the development of novel gene therapies for rare diseases. Although this is a professional MS, I do intend to participate in research during my studies at the University of Maine. Upon graduating, I plan to pursue a Ph.D. in Systems Dynamics to build decision-making models to determine leverage points towards more sustainable pathways and policies in conducting research. The current model creates an inefficient Bernoulli trial model, by linking specific funding sources to specific projects. If we link an extensive portfolio of funding sources, to an extensive biomedical research portfolio, stakeholder and public opinion interference are eliminated, hence achieving a more sustainable research business model. We may be able to revert Eroom's law, just like the mechanization of farming and the development of chemical fertilizers reverted the Malthusian catastrophe.