MDS Spotlight: Meet Cari Gostic, MDS Vancouver, Class of 2020
Prior to deciding to do a Master of Data Science degree from UBC, Cari Gostic planned on pursuing a PhD in climate studies but after 4 years of studies and a couple of summer research internships she decided that a Doctorate wasn’t the right path.
“I don’t think I would be very happy focusing on a single, niche topic for years,” Gostic said.
After graduation, Gostic got an analyst job on the consulting team with Risk Management Solutions, a catastrophe modeling company. While on this team, Gostic worked to streamline the integration of RMS software into clients’ workflows and complete custom projects like in-depth analyses and custom app development.
“I sat at the intersection of the client and the technical team at RMS, and was usually more heavily involved in the planning of the solution than the implementation,” she added.
Gostic decided to transition to a data science career because it combined everything she liked about research: uncovering insights, the thrill of discovery, working with new and interesting data but is extensible across all fields.
When it came time to choosing the right program to pursue her data science education, she looked at programs at the University of Vermont, University of Virginia, the University of Washington and UBC’s Master of Data Science program.
What led her to ultimately choose the UBC MDS program?
Gostic explained she was looking for a pure data science program meaning one that wasn’t specialized like business analytics and biostatistics.
The UBC MDS program won out because it was only 10-months whereas the other programs Gostic looked into were for 24 months.
“After having earned a salary for two years, it was hard to commit to more than a year without one. Therefore, the MDS program lasting only 10 months was a real bonus,” she added.
Another bonus was Vancouver itself. “As a nature lover, I was also looking to spend some time away from my native New York. Vancouver seemed like an awesome place to live, with a laid-back feel and easy access to tons of outdoor activities.”
Prior to beginning the program, Gostic prepared herself by doing a few coding challenge problems to remind herself of basic syntax in Python and R and brushed up on some basic statistics.
With the program wrapping up, Gostic reflected on the past 10-months.
“I entered the program with pretty significant imposter syndrome, especially since I don’t have a formal computer science background,” she said. “The fast pace of the program necessitated adaptability as we could never dwell on introductions to new topics. Since data science is so transient and constantly evolving, I imagine this will be a theme throughout the rest of my career. I’m leaving the program with confidence that I can pick up on new platforms, languages, methodologies, and frameworks on the fly.”
With the program’s completion, Gostic hopes to obtain data scientist and data analyst positions at environmental companies and non-profits.
“I’d like to contribute to making a positive impact on the world. I really like posing and answering research questions, and these job titles typically encompass these types of tasks,” Gostic said.
Cari’s Top 3 Tips on Succeeding in the MDS Program:
- Make friends with classmates: Especially when learning tough topics, it’s really nice to have a support group struggling along with you. You’ll spend a lot of time doing school work, so it’s also important to add some fun and laughs. Ask tons of questions and figure things out together.
- Don’t be intimidated: People come to the program from many different backgrounds, and it’s easy to get caught up in comparing your abilities with others’. Set goals for yourself, try your best, and be proud of your progress!
- Make weekly breaks a top priority: There will always be an assignment to perfect, an article to read, or a personal project to work on, but I really recommend designating one day a week where you don’t even open your computer. Grab drinks with friends! Take a walk! Call your mom! Trust me, it will benefit you in the long run.