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. Marc was a Fellow in our Spring 2016 cohort in San Francisco who’s now working at Google as a Computational Linguist.
Tell us about your background. How did it set you up to be a great data scientist?
I started life as a programmer, then I went back to graduate school at UC Berkeley for linguistics where I actually didn’t use my programming skills for a while. From there I did a neuroscience postdoc, where I started to use my programming skills a bit more. The neuroscience endeavor is, in many ways, a big-data endeavor. You get a tremendous amount of data from doing neuroscience experiments, and figuring out how to interpret and make sense of that incredible amount of data requires techniques that are not typical common in the behavioral scientific world, but are quite typical of machine learning and related data science fields. The way I would use those techniques as a scientist were not particularly sophisticated and while there is a lot of data when you’re analyzing neuroscience, it’s still orders of magnitude less than what people typically think of with big data.
So, when I started looking for job opportunities outside of academia, I realized that the way I talked about data analysis and the techniques that I used were not up to date. I wasn’t using the latest methodologies, tools, and terminologies that data scientists used even though the basic concepts were much the same.
What do you think you got out of The Data Incubator?
The key thing was being able to talk about data science intelligently in a way I hadn’t before, during interview. I was able to update my knowledge to where the field and industry currently is, which helped tremendously talking with prospective employers. I also learned about some ideas and concepts that helped make me be a better data scientist, reflecting the latest research within the field.
What advice would you give to someone who is applying for The Data Incubator, particularly someone with your background?
Could you tell us about your Data Incubator Capstone project?
How did you come up with the idea for the project?
What technologies did you use and what skills did you learn at TDI that you applied to the project?
What was your most surprising or interesting finding?
Describe the business application for this project (how could a company use your work or your data?).
And lastly, tell us about your new job!