Jaini Shah’s journey through Dartmouth’s residential accelerated MS in Health Data Science program is defined by curiosity, collaboration, and a passion for applying quantitative methods to complex real-world problems. A 2025 graduate, Shah has already built a career that bridges healthcare research and industry data science, while continuing to explore interdisciplinary ideas that first took shape during her time at Dartmouth.

During her graduate studies, Shah worked as a research assistant with Carly Bobak, MS, PhD, a Biomedical Informatics Scientist within Dartmouth’s Research Computing and Data Services team. That collaboration continued beyond graduation, culminating when Shah presented their research at the Pacific Symposium on Biocomputing, held January 3–7, 2026, on the Big Island of Hawaii.

At the conference, Shah presented a poster applying mathematical modeling techniques from social network analysis to better understand how biological genetic networks evolve over time. Rather than treating biological data as isolated snapshots, the research focused on capturing how early gene activity influences downstream biological processes. This approach offers new ways to uncover dynamic patterns in gene networks and better model how biological systems change.

“One of the best parts of this experience was being at the conference itself with my mentor, Dr. Carly Bobak,” Shah shared. “Talking to people about their work, seeing how others approach similar problems, and getting feedback from researchers outside my immediate field was very inspiring and exciting. It really reminded me why I enjoy research so much.”

Today, Shah is a Data Scientist at Vanguard, working within the company’s Forecasting Center of Excellence. In her current role, she builds and evaluates forecasting models that help teams make informed decisions across the organization. While her academic background is rooted in healthcare and biomedical data, Shah values the opportunity to apply her quantitative skill set in a new domain.

“Although I come from a healthcare background, I’m glad I found a role where I can apply my quantitative skills and really enjoy doing it as well,” she said. “Working for a big company that has a great impact on people is exciting, and I’m able to bring new ideas to the team while actively learning.”

Shah continues to collaborate with researchers in the healthcare space while applying forecasting and machine learning techniques learned through her financial data science work. This reflects the interdisciplinary mindset she developed at Dartmouth.

Reflecting on her graduate experience, Shah credits Dartmouth with shaping how she approaches both problem-solving and collaboration. “Working with the diverse labs and mentors at Dartmouth really helped me become a well-rounded person professionally and personally,” she said. “I was constantly able to apply new methods and approaches to my projects, which still shape how I think in my current role.”

She also highlights the impact of the people she worked with across campus, including Dr. Bobak, the Space Medicine Lab, the Brown Lab, Biostatistics Consulting, and the Dartmouth Cancer Center. These collaborations opened doors to conferences, research opportunities, and professional connections across the country.

“What stands out most to me is how interdisciplinary my experience at Dartmouth was,” Shah reflected. “I was constantly encouraged to pull ideas from different fields and see what happened when they came together. Applying social network concepts to biological data was something I never would have expected going in, but it ended up shaping how I think about complex systems more broadly.”

For incoming students, Shah emphasizes the importance of curiosity and connection. “Ask questions and network,” she advised. “Don’t be afraid to explore or step outside your comfort zone. Some of the most interesting opportunities I had came from trying something new. Take advantage of the accomplished people around you. Those conversations and collaborations can impact you more than you can imagine.”

Written by: Mia Soucy