When we first met Patrick, he was a student in our Data Science class. Since then, he’s taken on roles as a teaching assistant and lead instructor. He recently landed his dream job working as a data scientist for Oscar Health. Here’s his story in his own words.
What were you doing before taking our Data Science course?
After Efficiency 2.0 was bought out by C3 Energy, I was trying to expand my skill-set from statistics and into the realm of programming and computer science while helping start another company, Sealed. The Data Science class at GA was invaluable in helping build my skills and my career.
What is your favorite thing about data analytics?
I can find out almost anything with data. I can use data to help solve big problems like making energy efficiency easy with Sealed or improve diabetes treatment at Oscar. But it can also help solve small problems like designing an e-mail experiment to improve click-through rates or test assumptions about what motivates online readers.
You’ve been quite an asset to our New York Data Science community. What made you want to teach?
I had a lot of great teachers in high school in college; people who helped me learn the material and how to succeed in life. I want to be able to help students in the same way others helped me. I loved teaching statistics in grad school at Duke, so when I had the opportunity to TA and later teach at GA I knew I had to do it.
Congrats on the new job! Tell me about your role at Oscar Health.
Thanks! I’m joining Oscar as a data scientist to help make health insurance easier. Health policy has always been a nerdy passion of mine, and there are so many inefficiencies that I think it’s ripe for improvement. I know helping build a better health insurance company will be a lot of work, but I couldn’t be more excited about it. We have the opportunity to help people live longer, healthier lives and spend less time dealing with health insurance and more time doing what they love.
What has been your favorite project in your career thus far?
Helping build Sealed from an idea into a full-fledged company. Sealed combines machine learning principles, energy data and home characteristics to guarantee energy efficiency savings. I spent a long time writing algorithms and figuring out if this would really work, but now we’ve got a patent-pending machine learning algorithm and the company has pilot projects around the country.
Any advice for aspiring Data Scientists?
First, there is no set path to becoming a data scientist; people come from any background you can imagine but always with a passion for data. If you’re a business/data analyst you need to learn Python and R so you can tackle problems more efficiently, then dive into machine learning. If you’re a programmer you need to learn statistics and start developing your analytical instincts, because you can only get them through practice. Second, great data beats a great algorithm every time. The best programmer in the world can’t build a sound machine learning algorithm if the data is incomplete or comes from an unreliable source. Finally, never stop learning. This is a constantly growing field with new tools emerging all the time. If you’re sitting still you’re falling behind.
What’s your guilty pleasure?
Right now I’d say ice cream, since I’ve been eating more of it since I gave up caffeine 45 days ago. I cut most sweets out when I lost 80 lbs in college, but ice cream always gets me.
Take your passion for data to the next level.