Feature Stories 2024: McCord Murray '24: The science of math

McCord Murray '24, Data Science and Mathematics dual major.
Feature Stories 2024: McCord Murray '24: The science of math
McCord Murray '24: The science of math

Data science and math dual-major unlocks his potential

McCord Murray didn't graduate from high school. Four years later, he's maintained a perfect 4.0 GPA, studied abroad in Iceland, completed two internships, won awards in the Big Data Club, and tutored his peers while matriculating two majors.

For Murray, UMass Dartmouth provided a flexibility that allowed him to focus on his interests, and the resources to thrive.

Why UMassD?

Enrolling at Mass Bay Community College during the mid-term of his junior year of high school, Murray quickly found his stride in a setting more flexible than a high school curriculum. After earning an associate's degree with a concentration in mathematics, he began looking at four-year institutions to complete his bachelor's degree.

"I wanted to go to an in-state school because of its affordability, and at that time UMassD was the only public school in Massachusetts that offered an undergraduate degree in data science," says Murray. "I also loved the size of the school. I'm not someone who thrives in large lecture halls – I find 1-on-1 meetings to be more productive for learning and networking opportunities that can lead to personal letters of recommendation. Some of my data science classes are as small as 5 people."

Studying data science

What's exciting about majoring in data science?

"Data science is the science of math, and we're just entering the era of big data. This rapidly evolving field has become increasingly effective, profitable, and innovative for all disciplines and industries. Whatever your organization's mission statement consists of can be supported by understanding large data sets behind it. There are endless possibilities in big data."

How does your second major in math—applied statistics support your skill set?

"Machine learning is a statistical field. Looking at statistical models and algorithms helps us generate predictions of what data is going to look like. Understanding statistics complements data science well and the majors share some common curriculum, so I was able to do more in less time."

What are you hoping to do in data science?

"I'm hoping to work in quantum computing and computational biology to make molecules in the body easier to understand via computers. This method allows computers to create visualizations, observe and predict chemical reactions, and simulate results for drug discovery.

"There is a lot of promise for quantum computers to support pharmaceutical science. Instead of running animal and human trials that can take years and involve risk, algorithms can run simulations to predict what would happen at scale with increasing accuracy rather quickly."

What potential do data scientists have to change the world?

"Drug discovery is just one example of an industry data science can change for the better. Analyzing large data sets will also help develop self-driving cars, prevent cybersecurity attacks, forecast the weather and natural disasters, predict the stock market, and endless more possibilities. Anything you can quantify, data science can categorize, learn from, and predict."

Experiential learning

Murray's journey is a testament that unconventional paths can lead to extraordinary success. Not only has he thrived in an academic setting more personal and flexible than high school, he's also leveraged relationships with professors and the resources of a national research university into a packed résumé of diverse extracurricular experiences.


Murray stayed productive in his summer months, working in prestigious academic research internships at Columbia University and the University of Chicago, where he studied biostatistics, HIV data, and earned "his black belt in math."

"These programs gave me academic credit, research experience, and highly intensive coursework, which helped me decide that graduate school would be beneficial to my career path."

Peer Assisted Learning (PAL)

In his free time on campus, Murray earns money helping others solve math equations as a Peer Assisted Learning (PAL) Leader, which he describes as being somewhere between a tutor and a TA.

"Teaching is the best way to learn something. If you can explain something in different ways to different audiences, it enhances your own understanding of that topic."

Tell me about studying abroad in Iceland

"I would recommend studying abroad to any college student. I went to the International Programs Office Assistant Director Gina Reis and told her what I was hoping to study, and she suggested Reykjavik University, which is known for its strength in multiple types of machine learning. Studying language processing, deep learning, and cybersecurity from another country's point of view was fascinating."

What is your capstone research on?

"I'm working with a physics professor, Renuka Rajapakse to develop hybrid classical/quantum algorithms and a quantum generative adversarial network (GANS) to generate data. The goal is to develop a quantum algorithm that can match the data shown. This has been done very easily with classical algorithms, but doing so with a quantum algorithm would demonstrate the potential of quantum computers, which are currently limited by the amount of memory they can store in qubits."

What's your favorite part about the Big Data Club?

"Every year we compete in DataFest, a competition with a few other local schools that brings students from different experience levels and backgrounds together to compete in various categories. We won the Best Data Visualization for the 5th year in a row last year."

Looking back 

Do you have any advice for other students?

"Get to know your professors and ask them about opportunities in your major. Be enthusiastic about your subject, beyond just the lecture session. Experience and relationships with faculty who can write your letters of recommendation are what's going to help you find your next opportunity."


  • Professor: Gary Davis
  • Mentor: Alfa Heryudono
  • Class: "Math 332: Mathematical Statistics"
  • Extracurricular activity: The Big Data Club
  • Spot to eat: Birch Grill
  • Hangout spot: The library 1st floor
  • Event: DataFest 2022
  • Memory: Getting accepted into the Columbia summer program. I didn't think I'd get in, but my recommendation letters from faculty here were glowing and that set me apart.