Forging the Future of Data Science

Within the first few months of pursuing his master’s degree in data science, Andrew Huang was tasked with analyzing more than a quarter million reviews on the travel site TripAdvisor to identify common characteristics in travelers’ positive and negative feedback.

The project opened his eyes to the power and scalability of machine learning – a subset of the computer science field that examines pattern recognition – in making decisions, he said. "An analysis that would take humans years to complete was run on a computer using a machine-learning program in a matter of minutes."

This is one example of the applied-learning approach that is the hallmark of the new data science master’s degree program the University is offering in San Francisco through a partnership with Galvanize, an industry leader in competency-based learning.

Huang, who was part of the first GalvanizeU-UNH cohort that graduated from the program in May, started his career working in the finance industry, where he "saw a need for companies to learn from the data," he said. "I saw this master’s program as a perfect opportunity to go back to school to learn this skillset.

The program shines in the engagement of the faculty with the students," he continued. "They are with you on a daily basis, and they are fully committed to your learning and development.

He also touted the industry-oriented practicum component of the program and his internship opportunity at PowerScout, where he created the company’s first data warehouse using Amazon Redshift, an industry-leading business intelligence application used by companies such as NASDAQ, Nokia and Pinterest.

Classmate Mike Mansour described the San Francisco-based campus as a "little Disneyland for technology. I didn’t think a school could exist in such an environment. There is no better place to learn technology than in the center of the tech capital," he said.

His capstone project – "the most advanced level of machine learning I have applied" – involved figuring out and rewriting a broken algorithm for topic modeling, a way of identifying patterns in a collection of texts.

"It has gotten me a ton of attention and started many conversations – many around employment prospects," Mansour said.

As part of his internship at Elastica, he is doing anomaly detection, algorithm design and cutting-edge experimental research. His mentor there also spends time with him covering machine-learning topics that will come up in interviews and attending industry meetings that bring together leading machine-learning experts to discuss the latest topics.

"This program made my career," he continued. "I feel like I am approaching pro-level of data science, and it would not be possible without all the instruction and tools I received through GalvanizeU-UNH."

For Katherine Aquino, the program provided a way to pursue new opportunities and learn new skills after working for more than a decade in education and the nonprofit sectors.

I helped low-income students become the first in their families to attend college," she said. "After many years of advising students, I realized it was time to continue my own educational goals.

She previously earned a bachelor’s degree in physics from the University of California, Irvine, and she wanted to return to her science roots. "Data science is the science for real-world applications," she explained.

"The GalvinizeU-UNH program appealed to me because of its location, the industry-based internships and the networking opportunities that would be available from the Galvanize partnerships," said Aquino. "The program exceeded my expectations."

She is actively searching for career opportunities in data science while continuing her internship as a data science consultant at Elastica, a leader in data-science-powered cloud-app security. "I think my degree will help me transition my career into the tech industry," she said, "and prepare me to apply data-science solutions to real-world problems."