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. Isaiah was an Online Fellow in our Winter 2015 cohort who landed a job with one of our hiring partners, Truveris.
Tell us about your background. How did it set you up to be a great Data Scientist?
For one, doing my PhD taught me how to ask good questions. Questions that are useful and interesting, but at the same time answerable with a reasonable amount of effort. This is an important skill to have as a data scientist, because given a dataset, there are plenty of uninteresting questions you can easily answer, but answers to more impactful questions are often harder to get at.
In doing my PhD I also learned that getting to a nice result is often a matter of being persistent and following through with a lot of tedious work. This is also true in the context of data science. Real-world data is often messy, and getting to a nice actionable insight is usually not simply a matter of waking up one morning with a brilliant idea. I think my PhD background set me up to be a great data scientist in this regard.
What do you think you got out of The Data Incubator?
What advice would you give to someone who is applying for The Data Incubator, particularly someone with a physics background?
Second, I recommend working on a data-related project. Start with a seed of an idea and follow through with it until you have an interesting result. Getting your hands dirty and struggling through a project is the best way to learn. [Editor’s Note: for suggestions on data sources, check out our posts here and here.]
Could you tell us about the mini-projects you worked on? How did they help?
We were required to complete six mini-projects over an intense five weeks. These mini-projects covered the following topics: SQL, web scraping, graphs, machine learning, natural language processing, time series, and mapreduce. Completing the mini-projects was the ‘bootcamp’ part of The Data Incubator.
They were quite challenging, but also a lot of fun. The mini-projects were perfect for someone like me with a strong quantitative but not data-related background. They provided me with a comprehensive toolkit that I will undoubtedly use in the course of my data science career.
What was the Online Fellowship like?
For me the main benefit of being an online Fellow was being able to participate as a Data Incubator Fellow, without having to deal with all the overhead of moving to a new place. Being in LA, for example, I didn’t have to worry about purchasing a plane ticket, and I didn’t have to worry about relocating a second time if I ended up getting a job in a location different from my fellowship location. And of course, I didn’t have to deal with the awful East Coast weather!
What was the community like within the Online Fellowship? Did you meet any other Fellows?
Visit our website to learn more about our offerings:
- Data Science Fellowship – a free, full-time, eight-week bootcamp program for PhD and master’s graduates looking to get hired as professional Data Scientists in New York City, Washington DC, San Francisco, and Boston.
- Hiring Data Scientists
- Corporate data science training
- Online data science courses: introductory part-time bootcamps – taught by our expert Data Scientists in residence, and based on our Fellowship curriculum – for busy professionals to boost their data science skills in their spare time.