Dor Chavoinik

I’m a Data Scientist: Dor Chavoinik

Double Major: Society and Environment Conservation, Resource Studies


Question: How did you first get interested in data science?

Answer: I first became interested in data science because of its ubiquity. While not everyone is aware of how data science tools coexist with their lives every day, it became impossible to ignore when I transferred to Cal two years ago and heard the "big data" buzzword often. As I started researching certain terms, tools, and even course offerings around them, I realized how important data science was in terms of being a general consumer and producer of data, as well as how it was relevant for my academic domains (including global development practice, environmental and social change, and emerging "green" technologies).

Data science deserves our attention for its potential, as well as a constant awareness of how its use might benefit or harm people or groups of people disproportionately.

Q: How have you been using data science? Any surprises?

A: My introduction to using data science has involved exploring powerful data visualizations, as well as leaning on the predictive potential of data science for small projects using large datasets. One of the most surprising aspects has been how much of a thriving community exists online for data science projects, and it has also been tremendously helpful for me to take my socioeconomic studies of theories and go "on the ground" by exploring trends in data that serve as indicators for health or economic well-being. For example, there’s a surprisingly large and thriving community of folks who just place sensors in their backyards that provide spatial data that can help us understand environmental problems, such as air pollution. It becomes clear that this is an increasingly invaluable way to know the world. DS deserves our attention for its potential, as well as a constant awareness of how its use might benefit or harm people or groups of people disproportionately.


Q: How do you envision using data science in the future?

A: While I plan to develop my skills and scope in using data science tools to work on solving environmental and social problems, I especially enjoy thinking about how to maximize its potential to progress justice. This includes a balance of using the tools to address pressing social justice concerns while continuing to develop the sense of ethics and context that must inform this type of work, and also imagining how it might conversely be abused. I think there is room for DS in understanding refugee flows, pollution and health, and renewable energy services for example, but it is also impossible to address these problems effectively without considering the contexts of equality, agency, or racism.  


Q: Any advice for students curious about data science?

A: My advice is to explore your curiosity and at least dip your toe in the water. It is so valuable in beginning to understand how you are already part of the massive ongoing data generation efforts, not to mention how it will likely show up as a valuable tool in your field of study. Even if you think you won't be "good" at it or you are not a quantitative person, you will hopefully be as surprised as I was despite thinking the very same things! Increasingly, we are seeing that data science affects almost all of us. I think that if you are interested in the allocation of power in the world, understanding how "big data" is being used and who the experts are who have a say on major ethical dilemmas such as privacy and security, it is important to explore data science and how it in truth is not a democratized ownership of information.