Why Data Science?
When I was a little girl I knew precisely what I wanted to be when I grew up: a doctor. Though my interests changed over time, my career plans did not. I began college on the pre-med track with a major in Psychology, determined that I already had it all planned out. I was going to graduate with my B.S. in Psychology, attend medical school in the following semester, become a neonatal surgeon (a surgeon who specializes in infants and newborns), and spend the rest of my career making the world a better place.
I think you can guess where I’m going with this.
As they so often do, my plans changed. I struggled with Chemistry, finding the classes much more difficult to understand than they had been in high school. I found myself stumbling in Biology, a field in which I’d previously had little issue grasping the material. I pushed through the best I could, but I found myself losing steam in my dream.
Then, I took a class called Human Factors and everything changed. I volunteered to become a research assistant in the professor’s applied cognition lab and fell in love with research, so much so that I even spent my last semester conducting my own study on information recall of airline safety demonstrations. In collecting and coding the data I found my stride with analytics, and then completed an online data analytics course via General Assembly. Having discovered that this was the field for me, I applied for an internship in market research analytics with the Walt Disney Company, where I had previously worked in the parks.
During the year I interned at Disney, I had the opportunity to cooperate with multiple lines of businesses to present actionable insights from analysis of quantitative survey data and qualitative research. I enjoyed the work, but I often found myself asking questions about the data that I did not have the skills to answer. I observed some of the work data scientists in my department were doing, and through them I learned about boot camps that teach the skills needed to answer the exact sort of questions I had been asking.
I returned to General Assembly, this time enrolling in the Data Science Immersive program. There I developed familiarity with real-world applications of data science principles and best practices. The pure interest and enjoyment I experienced in learning Python, Bayesian statistics, and machine learning confirmed that data science is the field in which I want to make my career. The sheer volume of information I acquired in this program is mind-boggling, but each new skill I learned left me thirsting to know even more.
People often ask why I chose data science, but I believe that in my non-linear and rather untraditional career path I have discovered that it chose me. Though I am no longer the bright-eyed, naive freshman wanting to save the world (and all the babies in it), I remain an optimist wishing to leverage my knowledge to leave the world a little better than I found it. I believe wholeheartedly that when we tap into our vast data stores that contain so many solutions just waiting to be uncovered, we are making the world a better place.
It may not be saving babies, but it’s still pretty great.
