I have always loved a story. In a good story, characters do exciting and interesting things, but the most compelling part is their motivations: why?
My own story took time to develop, and it centered that exact same question. After four intensive years of engineering coursework, I watched my classmates passionately plan startups and prep for Google interviews, but while I understood that was what I was supposed to do, I couldn’t find my motivation. Instead of at a desk coding, I yearned to be out in the world, learning what it needed from me.
I traveled to Ireland, studied acting for two years, and learned about a new history and a new culture. To make ends meet, I made crepes in food trucks, learned (as most actors do) the art of making coffee, and spent evenings waiting tables. I met people. Then, in 2020, when I had shows lined up and an acting career starting, COVID-19 interrupted everyone’s plans, including my own. No longer able to attend rehearsals and meet new faces over the till everyday, I returned to coding.
This time, it felt different. This time, I had spent time singing with Irish farmers and made distanced visits to grandparents that I feared could be the last. I had taken the gloves off, seen the world, and now I knew the impact I wanted to have. I knew why.
Technology, I found, is at its best a fundamentally human endeavor. It helps us live the healthiest, most connected, richest lives we can.
Data is the most human resource we have. In essence, it is the story of us, of the world, of the environment, of history. I work with data because I want to tell that story.
How does my background impact my approach to Data Science?
I am results-oriented.
As on stage or film, the results are what matters. Whether ingesting, analyzing, or visualizing data I never forget that my work is part of a broader process. My work needs to feed seamlessly into both the next step in the process and the final product: actionable insights.
I adapt to the unexpected.
Things don’t always go the way we expect. Sometimes your scene partner accidentally skips to the middle of the scene and sometimes data is in an entirely different format. Or your hypothesis is false. In unexpected situations, I am used to adapting and solving problems creatively.
I work collaboratively.
As an actor, it is key to remember that no matter how good you are… if there’s no light, they can’t see you. In other words, we all rely on one another to get the show to an audience. There is no person in the process, from the director to the crew that cleans the stage after hours, that is non-essential. The same is true with a data project. From collecting to acting on insights, the process requires trust and collaboration.