After a successful career teaching mathematics from the elementary to college level, Melissa Phillips decided to make a pivot in her career to data science.
Phillips graduated from the School of Data Science in 2020 and is currently a Data Scientist and Community Engagement Coordinator at Commonwealth Computer Research, Inc. (CCRi).
“I was taking professional development courses for teaching and doing some courses online,” Phillips explained. “I realized that I was preparing my students for the job that I wanted.” Phillips took her students to a math competition where she met a data scientist who talked about her work. “She [the data scientist] explained how her job combines math and computer science and I thought, that's perfect for me.”
Phillips was teaching in Charlottesville at Tandem Friends School and when she learned UVA had a master’s in data science, she did not hesitate to apply.
“I was in Charlottesville at the time, so the location was convenient and attending UVA was amazing,” Phillips said. “It was a good fit for me because I do better with in-person contact with professors and other students.”
Phillips described the M.S. in Data Science program as challenging and fast-paced, but loved learning alongside her classmates and from SDS faculty.
“The faculty were very kind and generous with their time, and I loved having the cohort experience. Just having other people to turn to who were solving the same problems was so helpful.”
She also noted that she was not alone in the career pivot. There were quite a few students in her cohort looking to switch into a data science career.
“Some of my classmates were coming from computer science while others already had a data analytics background. But there were several of us who were career transitioners,” Phillips recalls. “It was really neat to have classmates from such a wide variety of backgrounds in the program.”
As Phillips learned data science tools and techniques, she realized advice she had given her own students for years was applicable for herself.
“I learned that talking through problems with my classmates was incredibly helpful,” Phillips admits. “I read every textbook I could get my hands on. I asked lots of questions. These were the exact things I had told my students to do as a teacher.”
Phillips accepted a job at Commonwealth Computer Research, Inc. (CCRi) in Charlottesville after graduating. Looking back, she admits navigating the career change was both daunting and exciting.
“Being a teacher becomes such a deep part of who you are,” said Phillips. “I knew I needed to change because I was very stressed out and it was taking a physical toll. That motivated me to make the change. Classmates in the MSDS program and colleagues at CCRi have also helped me transition smoothly.”
CCRi is a geospatial data science company, founded by Don Brown, Senior Associate Dean for Research and Quantitative Foundation Distinguished Professor in Data Science. Brown also founded the Data Science Institute which led to the formalization of the School of Data Science in 2019.
“CCRi works with maps and analyzes what vessels are in the ocean or what aircraft, planes, and helicopters in the air are doing,” Phillips explained. “Data scientists at CCRi help control the flow of data. We analyze things so we can start to see patterns in how vessels and vehicles are moving. We also look at other kinds of imagery and sync that up with the other geospatial data on the map and just try to unpack a little bit more about what vessels and aircrafts are doing.”
Phillips specifically does software engineering on trackers for vessels and aircrafts. With this experience Phillips explains “how great it is to learn from more senior developers and see how they manage code.”
The biggest piece of advice Phillips gives to future data scientists is about the importance of communication.
“It is hugely important that while you grow your technical skills, you also foster the soft skills. Data science is quite technical, but never forget the soft skills of working with people, working in teams, and being able to communicate those technical details in an understandable language. This has been a great transferable skill to bring from teaching to data science."