
At The Data Incubator we run a free eight-week data science fellowship to help our Fellows land industry jobs. We love Fellows with diverse academic backgrounds that go beyond what companies traditionally think of when hiring data scientists. Liang Shi was a Fellow in our Fall 2016 cohort in Washington, D.C. who landed a job with our hiring partner, Afiniti.
Tell us about your background. How did it set you up to be a great data scientist?
I obtained my PhD in turbulence theory at Max Planck Institute for Dynamics and Self-Organization in Germany. Afterwards I did a postdoc on turbulence modeling of atmospheric boundary layer flows at the National Institute of Standards and Technology. Both problems require extensive numerical simulations and data analysis using parallel algorithms and computing. The largest simulation that I have performed, ran on 5000 cpu cores for 3 months, generating around 10 Terabytes of data. These experiences gave me my first contact with ‘big data’ and equiped me with a toolset of data analysis. Most importantly, as a scientist, I am extensively trained on asking the right scientific questions, designing the experiments or simulations, using the good visualiztion tools to explore the data, and then giving nice presentations to deliver the findings. These are actually the essential savoir-faire to be a data scientist.
What do you think you got out of The Data Incubator?
Since I had always been in academia before, TDI is like a window to the industry, a bridge walking me smoothly from the academic world to the industry world. Through a series of activities like panel discussions and the alumni party, TDI offered me a great platform to know what kind of problems companies are trying to solve, what skills they are looking for, what the daily life looks like, etc. Moreover, TDI provides valuable guidance in the whole process of job searching, and last but not least, the chance to work with a bunch of very smart people.
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