Data are becoming the new raw material of business
The Economist

Turning Bold Questions into a Data Science Career at Amazon: Alumni Spotlight on David Wallace

At The Data Incubator we run a free eight-week Data Science Fellowship Program 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. David was a Fellow in our Winter 2016 cohort who landed a job at our hiring partner, Amazon.


Tell us about your background. How did it set you up to be a great Data Scientist?

Before joining The Data Incubator, I completed my Ph.D. in chemistry at Johns Hopkins University, where I focused on the design and synthesis of new magnetic materials. My work gave me the opportunity to work alongside scientists in many different disciplines, and exposed me to a vast array of experimental techniques and theoretical constructs. From a data science perspective, this meant that I was constantly encountering new types of data and searching for scientifically rigorous models to explain those results. As the volume and complexity of these datasets increased, graphical data analysis tools like Excel and Origin weren’t making the cut for me, and I gradually made the transition to performing data transformation and analysis entirely in Python. That was a big technical leap that took a lot of time and frustration, but I think it ultimately made me a better researcher.

From a research perspective, working in a vibrant academic setting also meant learning how to ask bold questions, even at the risk of sounding stupid in front of a large group of mentors and peers–something I’ve done more than I care to admit. For me, finding the right question to ask is just as important as having the technical expertise to find an answer, and that’s one of the things that makes Data Science so exciting.


What do you think you got out of The Data Incubator?

TDI provided the opportunity to work with an incredibly intelligent and motivated group of people on difficult problems that were directly relevant to Data Science. In the DC office we were constantly troubleshooting problems together, trying new ideas, and helping each other to improve as Data Scientists. This collaborative atmosphere, coupled with a very strong curriculum and knowledgeable mentors, really helped me to take my programming and machine learning capabilities to the next level. Aside from the technical aspects, TDI was just a fun experience, and I made some great friends with whom I’ll stay in touch throughout my career. Shouts out to Team Werewolf and Team Chupacabra!

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