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. Matt was a Fellow in our Winter 2016 cohort who landed a job with one of our hiring partners, 1010data.
I defended my PhD dissertation at Washington University in St. Louis, a few weeks before coming to The Data Incubator. I was part of the MAPLE lab in Energy, Environmental, and Chemical Engineering (I know, it’s a mouthful). Our lab focused on physics-based electrochemical modeling, mostly geared toward Li-ion batteries.
For my main dissertation project, I studied how batteries age under different real-world cycling patterns. Most cycle life estimates for a battery are based on simple constant charge and constant discharge patterns, but lots of applications (such those experienced by batteries in electric vehicles or coupled to the electric grid) do not have simple cycling patterns. This variation effects the life of the battery.
Both through model simulation and long-term experiments, I had to analyze battery characteristics over thousands of cycles and pick out important features. This type of analysis along with programming computational models that were used to create these data sets helped give me a background to tackle data science problems.
Additionally, I think that working on my PhD projects allowed me to gain experience in solving unstructured problems, where the solution (and sometime even the problem/need) are not well defined. these type of problems are very common, especially once you get outside of academia.