I’m a Data Scientist at a small data mining consulting company in DC called Elder Research. I turn data into numbers, numbers into words,
words into stories and stories into action for my clients.
I started my professional career on the Economics PhD track at the Federal Reserve Board. I took some abstract math classes to prepare, but then I started taking some cool applied statistics courses at Georgetown U. I started getting good (and interested) in programming and less interested in abstract academic research. I decided to leave the Fed to finish my Mathematics & Statistics Master’s program at Georgetown U and work as a Data Scientist at Elder Research, a small consulting firm specializing in data mining and predictive analytics. I love starting projects from scratch: working with clients to identify their problems, strategizing analytic approaches, creating models using machine learning methods and operationalizing these models to truly drive behavior and improve decision making.
My career path has gone something like this:
I started undergrad doing international relations thinking big picture with ambitions to be a diplomat of sorts.
Then I got hooked on economics.
Then I realized economics is really math.
Then I realized I was better at computer languages than abstract mathematical languages and foreign languages.
Then I realized I actually liked computer languages; that I could actually be more creative and powerful with data and code.
Then I got a job where I get to learn as much about data science and machine learning as possible.
Then I realized building models for people is harder than just building models for people.
Then I started turning numbers into words, words into stories and stories into action.
Then I started building this website.