Tuesday, January 29, 2013

Personal Note: Adjustment in Career Path Towards Data Science

I want this blog to be about the work that I do and not about my person. But there will be a change in the the content of the blog which can only be explained by the change in my professional situation. So far, computational topics have been about FDTD simulation, molecular dynamics simulation, python, and scientific computing in general. I've been a graduate student at Vanderbilt University for four and a half years where I've learned an incredible amount in the areas of nanoscale science & engineering and computing, both of which are areas I did not have the background for. This was all under a mechanical engineering degree but I'm leaving with 'just' a master's degree in "mechanical engineering" as I did not pass my PhD qualifying exam in...(classical) mechanical engineering. Now, I was quite disappointed for a while since I enjoyed my research very much and was looking forward to making contributions to energy conversion device research using computation.

But, looking back only a few months later, I'm glad it happened. I felt that I had a programming talent lurking inside me as I was conducting my computational research and it would be wise to enhance my computational skills which would qualify me very well for certain job types. So, I've started a (second) master's in computational science at George Mason University customizing my curriculum for 'big data'. I've identified 'big data' as a field that I want to get into because I feel that I have the right combination of communication, business, and technical skills to be successful in this field. This potentially means that I might turn my back to science and engineering as an application area of my skills which is something a bit discomforting to me as I've always seen myself as a scientist and engineer. At the same time, advanced scientists and engineers have the potential to be great data scientists.

What does this mean for the blog? I still expect to post about (pure) scientific computing but not about applications like finite-difference time-domain simulations and molecular dynamics simulations. Python will stay with me as a base of my programming skill but it will be complemented by other computing languages that I will learn like SAS, R, C, and Fortran (working on working in HADOOP!). This is what I'm able to predict for now.

Ending with a positive personal note, for most of the past decade I've been striving to get into a job type that I want. I'm very optimistic that I'm almost there.