Muyao (Jenny) Lin’s path into biostatistics was not a straight line, but it was shaped by a clear goal: finding meaningful ways to work with data to answer real-world questions. Now a Research Associate with Virginia Tech’s Center for Biostatistics and Health Data Science (CBHDS), she brings that mindset into every collaboration, helping investigators translate complex datasets into actionable insights.

Lin began her academic journey studying mathematics but quickly realized she was looking for something more applied.

“I started with math in undergrad, but there was a lot of theory and proving,” she explained. “I wanted something that felt more like working with data and identifying patterns, so I transitioned into statistics.”

That shift ultimately led her to graduate-level coursework in statistics, where a consulting course helped define her career direction. 

“We worked with faculty and students on their research projects, learning about their goals and helping them figure out how to approach their data,” Lin said. “That experience showed me I really enjoyed the consulting side of statistics.”

After graduating, Lin initially pursued traditional data analyst and data scientist roles before discovering opportunities more aligned with her interests in research collaboration. That search led her to CBHDS, where she now supports a wide range of projects alongside Assistant Director Alicia Lozano.

In her role, Lin works closely with investigators from the earliest stages of a project through results and manuscript development.

“We meet with the PI to understand their goals and what they want to learn from the data,” she said. “Then we clean the data, analyze it, and go back and forth with them to make sure the results align with the research questions. Eventually, we help support the final manuscript.” 

For Lin, the most rewarding part of the work comes from seeing progress at every stage of a project.

“For each step, I’m creating outputs like tables or identifying issues in the data,” she explained. “Those small results are rewarding on their own, but it’s also meaningful to see how they help the investigator move forward.”

Her work has exposed her to a wide variety of research areas, from survey-based studies on quality of life to more complex longitudinal data collection efforts.

“That kind of data is very different from a one-time dataset,” she said. “It requires learning new approaches, but that’s something I really enjoy.” 

That willingness to continuously learn is central to both her work and her advice to others entering the field.

“You need to understand that this type of work involves constant learning,” Lin said. “Every project is different, and you will need to adapt. If you enjoy learning new things, it can be very rewarding.”

Collaboration is also a defining part of her role, and Lin emphasizes the importance of communication and shared understanding between statisticians and investigators.

“Mutual understanding is really important,” she said. “Investigators may have specific expectations, but we must work with what the data shows. At the same time, we need to understand their perspective. Communication helps make that process successful.” 

Lin’s approach to collaboration is shaped by her flexibility and openness to different perspectives.

“I think being flexible is one of my biggest strengths,” she said. “It helps make collaboration easier, whether that’s adjusting to changes or working through different ideas with a team.”

Ultimately, what drives her work is seeing that collaboration lead to meaningful outcomes.

“When the results we produce match what the investigator is looking for and help them move forward, that’s when I know this is what I want to do,” Lin said. “It feels like a win for everyone involved.”