Tell us a bit about yourself.
I am a civil engineer and geographic information systems (GIS) analyst living in New York City. I am pursuing the Master of Information and Data Science (MIDS) degree full time to fully immerse myself in the program. I have a bachelor’s degree in civil and environmental engineering from Duke University.
For many years, I worked as a water resource engineer in the Bay Area, dealing primarily with sustainability, alternative water resources, and green infrastructure. My work with geospatial data and spatial analysis enabled me to work with data across diverse disciplines like climate science, urban planning, and economics. Ultimately, I want to find better ways to measure and analyze actions in dense, complex urban environments.
What initially attracted you to the data science field?
Coming from an industry that relies on data and analysis but does not utilize data science, I found that the increase in data outpaced my ability to analyze it, leaving many questions unanswered and even unexplored. While researching ways to do more with data and provide better analysis, I learned about data science and it seemed like a natural next step for my career.
Why did you decide to pursue a Master of Information and Data Science?
After learning about data science, I decided to make a transition from my career as a civil engineer into a focus on data science. Coming from outside the tech industry, I felt that I had a lot to learn and that a master’s program would be the best way for me to comprehensively study the many topics that were new to me.
Why did you choose datascience@berkeley?
I chose datascience@berkeley because of the flexibility offered by the program, as well as the well-rounded curriculum. I like that the program was not simply about coding and data systems. The emphasis on aspects of data science with consideration for real-world application, like ethics and communication, created an entire package that appealed to me. The ability to learn remotely from an institution like UC Berkeley was also compelling, as I could structure my course work each semester around my personal and professional life while attending such a prestigious institution.
What is the I School's advantage?
Being online is a tremendous advantage for the MIDS program at the School of Information (I School). It provides access to students from around the world, bringing in a very high caliber of professionals from diverse backgrounds. This leads to many different perspectives and a rich learning environment. MIDS students have sought this program out and are extremely engaged and looking to learn from both the program and their peers.
What has been your favorite course at the I School and why?
I am still early in the MIDS program, but I am really enjoying Behind the Data: Humans and Values. It has been fascinating to learn about the larger context within which our work exists. It is easy to get caught up in trying to complete your analysis and forget that the data represents people. The class highlights the responsibilities we have both as stewards of vast amounts of personal or sensitive data and as the synthesizer of information that will be used to infer important decisions. This provides an excellent perspective of what we are doing as data scientists.
What is an information challenge that intrigues you?
I have worked with spatial data in urban spaces for many years, and I am fascinated by how interconnected cities can be. There are so many things happening in overlapping spaces, and data from disparate sources can show correlations interplaying between seemingly unrelated aspects of the urban environment. Synthesizing this data, finding relationships, and utilizing it to inform urban policy and development is a data challenge I want to work on in the future.
Which skills and tools covered by the program do you find most appealing? Why?
I like that the program includes the practice of communicating results and analysis clearly, including presentation skills and visualization. It is imperative as a data scientist to communicate effectively. You may have the most accurate or impressive results, but it is all meaningless if your audience does not understand. It is this last crucial link in the chain that is often overlooked.
What surprised you most about the online learning environment?
I was impressed with just how much interaction there can be both within and outside of the live class sessions. The online platform allows for discussion boards as well as chat and the ability to connect at any time. Engaging in meaningful conversations with your instructors and classmates provides a more in-depth knowledge of the content and develops your network with peers.
What advice do you have for aspiring information professionals/data scientists?
I recommend aspiring data scientists pursue knowledge and education on topics beyond just the technical skills associated with data science. Software and systems will change over time, but a problem-solving mentality and the larger perspective of the impact of our work are underappreciated and integral to data science.