We love Fellows with diverse academic backgrounds that go beyond what companies traditionally think of when hiring Data Scientists. Justin was a Fellow in our second cohort who landed a job with one of our hiring partners, Palantir.
Tell us about your background. How did it set you up to be a great Data Scientist?
What do you think you got out of The Data Incubator?
Finally, I got to meet and became friends with the other Fellows, as well as everyone involved with the Data Incubator. It was encouraging to be surrounded by so many like-minded people, and it will be exciting to stay in touch with them as they go off to do interesting things in different industries.
What advice would you give to someone who is applying for The Data Incubator?
What about your work in mathematics training is useful for finding a data science job?
Can you describe the project you worked on at The Data Incubator?
First, I wanted a measure of how long any given cab ride in the city at any given hour during the week could be expected to take. But not just an average—I wanted to estimate the distribution of times to get a sense of how long it would take, for example, in slow traffic. For trips where it’s important to not be late, knowing the worst case is more useful than just knowing what is typical.
Second, I wanted a visualization of how difficult it is to hail a cab at different times of day. This depended on inferring the number of available cabs in an area at each time of day, something not explicitly present in the data.
The natural way to convey this information was to build a website, which ended up being at least as much work as the analysis! It’s very satisfying, though, to build something so quickly and see that it actually works for the most part.