I took a very roundabout way to get started on my journey into learning data science. Now that I’ve officially set off on this path, it feels right. I’ve been trying to sort out what I want and need from a career since I graduated from college in 2013. I went to grad school thinking I might like to be a professor. I have always enjoyed learning, and I knew that to have a fulfilling career I would need to continue learning new things and being exposed to different ways of thinking. Eventually I realized that higher academia was not quite the right path for me, even though there were aspects of it that I really enjoyed.
Grad school was where I was first introduced to data science. I learned to do various analyses in R for my thesis on desert tortoise behavior and personality. However, I was not able to lay as strong of a foundation in coding and statistics as I would have liked. That was definitely something I regretted, and I am thrilled to have the chance to rectify that now while at Flatiron School.
After grad school, I tried my hand at being a high school science teacher. Teaching seemed like a meaningful way to combine my love for science and enthusiasm for learning. It was a very enlightening experience. I learned to work with and for people in ways that were very different from what I had experienced before. The work was both extremely demanding and rewarding. Teaching also helped clarify some things about myself and what I need to put into and get out of a career.
So why data science? Grad school showed me that using models built with code to ask questions and test various hypotheses is something I really enjoy doing. I love how you can continue to make adjustments to ask different questions and how those questions tend to lead to more questions. I also thoroughly enjoy the challenge of learning and selecting the best tools for the job in a field that will continue to evolve rapidly. Data science is also very appealing in that there is hardly ever a single “right” or “best” way to go about tackling a certain problem. This makes collaborating with others on a project very rewarding. Everyone will have a slightly different style, a slighty different way of thinking and coding, so there is always something you can use to learn and improve. While teaching high school pushed me to develop skills for working with diverse groups of people, I look forward to being in a field where I can routinely collaborate with smaller groups of people (as opposed to engaging a room of 30+ students) to complete projects. In short, I’ve decided to take a leap and make a change in my life because I know data science is something I enjoy that is well-suited to my skillset and personality.