Category: Applied Economics and Statistics
UD online master’s program in applied statistics alumna Anaise Higgins took the unconventional path to data science
November 21, 2024 Written by Nya Wynn | Illustration done by Katherine Young
After finishing the University of Delaware’s online master of science in applied statistics program, Anaise Higgins, a UD Class of 2023 graduate, has catapulted herself higher up in the world of data science.
After graduating with an undergraduate degree in mathematics from another university, Higgins was researching master’s programs that would allow her to work full time while simultaneously building the advanced statistical skillset needed for careers in data science.
“I knew I needed to find a program that was asynchronous and geared toward working professionals,” Higgins said. “As I was doing my research, I came across the University of Delaware's online master's program in applied statistics and found that it met both those criteria.”
Before going back to school for her master’s, Higgins was working as a data analyst, but had a strong desire to build upon what she studied during her undergraduate degree by learning more about the theoretical foundations of statistics and machine learning models.
Higgins, who resides in Georgia, valued flexibility and UD’s online program had it. She worked as a data analyst all while earning her graduate degree.
“I really liked the variety of core courses and elective courses offered and felt that the program allowed me to deepen both my applied and theoretical statistics knowledge while also enabling me to continue to pursue my career and work towards becoming a data scientist simultaneously.”
Higgins began working as a data scientist at a top national insurance company shortly after she graduated in 2023, citing that everything she learned from the program was critical to getting her that high-level position.
“After finishing UD’s online degree, I had a much deeper understanding of the theories behind statistical methods and machine learning models,” Higgins said. “This gave me the knowledge and skills needed to become a data scientist who specializes in statistical modeling.”
Since the program launched, this flexibility was a chief goal of Tom Ilvento’s, professor in the Department of Applied Economics and Statistics and the architect of the department’s online statistics program. Whether it’s starting your coursework, setting your schedule, or deciding when they take each class, Ilvento wanted the program to fit each student’s schedule and current knowledge and skill level.
“Often, when we admit a new student, I’d meet with them to see where their starting point is,” Ilvento said. “If you’ve been out of school for five, eight, even ten years, you might be nervous about taking an exam, so I would feel people out.
“And I think that was important, just so that people getting started can build their confidence as they continue throughout the degree into the more difficult and demanding courses.”
In the online graduate program, the majority of the students in the program are either already working with data in their careers but they want to overcome some of their limitations, or they’re seeking a master credential to make them more competitive in the job market.
Higgins was a blend of both of these types of students. She was already working with data, but through UD’s program she gained the skills essential for her current career as a data scientist. Higgins credits the array of core and elective classes that the Department of Applied Economics and Statistics offers.
“The most valuable part of the program was the knowledge I gained in a variety of statistical methods and machine learning models such as linear regression, logistic regression, random forests, cluster analysis and survival analysis,” Higgins said. “Having a deep understanding of how to build these models, their assumptions and their parameters is what I’m using the most as a data scientist.
“It was also valuable that the program offers coursework in R, Python and SAS, with flexibility in some of the courses regarding which language you use to complete the assignments.”
Two extremely applicable courses are Mathematical Statistics (STAT 671) and Probability Theory in Statistics (STAT670).
“I enjoyed those courses because they showcased the intersection between statistics, linear algebra, and calculus,” Higgins said.
In comparing UD’s online degree to a more traditional master’s degree in applied statistics, Ilvento does not see much of a difference. Students build a deep theoretical foundation of statistics while also getting hands-on experience working with data that oreos them for a career in data science.
“I don’t see a lot of difference between our online and live programs in terms of content and what we do,” Ilvento said. “Our traditional live degree is a little more theoretical, and our online is a little more applied, but both of them have aspects of both. So any career working with data analytics, a student would be prepared to do.”
Many experts in the field are awaiting to see the impact that artificial intelligence has on applied statistics, but Ilvento feels that traditional statistical methods are here to stay.
“Companies have large datasets and they need someone to help make sense of it and help make decisions with it,” he said. “And this degree would provide those insights, while also making sure they’re learning software, different programming techniques and also machine learning techniques.”