Maria Francesca Arruda de Amaral

For Maria Francesca Arruda de Amaral, data science can be a critical tool in understanding patterns in crime, policing, and how laws impact different regions. “There’s just so much information out there,” she says. “Part of doing responsible data science and responsible research is knowing how to interpret the data. And a great part of the field now is also related to ethics, and making sure algorithms are not relying on problematic data.” Francesca first encountered data analytics as an undergraduate at Penn, when she used the programming language R to analyze gun laws, deportations, homicide rates in Latin America, and policing interventions in Rio de Janeiro. Although she graduated in a year of remote learning, virtual commencement, and hiring freezes, Francesca landed a full-time position in Penn’s Department of Criminology, where she now applies these skills to research projects on progressive prosecution with the Philadelphia District Attorney’s Office. But her dream is to continue her studies, so when she learned that one of her colleagues was taking courses in the Penn Alumni Program, Francesca leapt at the opportunity to prepare herself for graduate school.

In the Penn Alumni Program, Francesca has studied statistics and taken several courses in calculus. “As I started my job, I realized I missed math,” she laughs. “In social science, some things are very subjective, but math is very stable. In high school I would do math Olympiads and I really enjoyed that, but I ended up not taking as much math in undergrad.” The math courses not only reconnected her to a favorite subject, but helped her understand more of the logic and theory behind the methods she uses in statistics and data analytics. “In a pure math or stats class, we’re not necessarily talking about the ethics of using it in the real world. The professors emphasize how to know when those models are applicable and when you should be using those functions, what are the constraints, what you should assume and shouldn’t assume—and that ties into the real world,” she says. “That’s why it’s good for me to take these fundamental classes in the Penn Alumni Program. Going back to the assumptions underlying your models is a step that people don’t always take, but it’s an important one.”

Francesca also took a course in data mining, and an evening course in Python and Java from Penn Engineering, expanding her familiarity with programming languages alongside both undergraduate and graduate students. “I don’t use Python that much, but our data engineer uses it, so it’s nice to be able to read his code,” she says. “And it helps on the job to better know the models that we’re using and to write papers in a more substantive way.” Francesca’s self-directed curriculum has also broadened and refreshed the knowledge base she brings into work. While co-authoring a paper on gun statistics with her Principal Investigator (who had also taught her statistics before) and another faculty member, “We were looking for methods to solve a particular problem with faulty data,” she recalls. They attempted to solve the problem with a divergence measure, but Francesca suggested adding on a bootstrap method that she was learning about in class. “And we ended up using bootstraps!” she concludes. “So, it was cool to be able to bring that into it.”

Francesca’s ultimate goal in taking classes in the Penn Alumni Program, however, is to distinguish herself as a prospective PhD candidate. She is applying to graduate programs in public policy as well as criminology programs with more of a quantitative focus. “I do want to keep studying crime in Latin America. It’s something I hope I can contribute to my country in some way,” says Francesca, who grew up in Brazil. “That’s why I took some of these classes: they complement my research experience, and I can demonstrate a more quantitative background than my undergrad majors show.” She also expects to continue studying programming at the graduate level, which was another reason she took a course in Python and Java. “It’s to save some time,” she says. “Not that the course will give me graduate credit, but it will give me the background so I can jump into higher courses.”

Although taking intensive quantitative courses while working full time is a rigorous schedule, Francesca appreciates the familiarity of her alma mater. “I trust Penn. I know how to navigate the school, having the same PennKey and PennCard. I know some of the courses and their professors,” she says. “I would have figured it out somewhere else, but it’s nice to already have some prior knowledge about the place and things to expect.” She also appreciated how seamlessly her post-baccalaureate studies fit into her life after graduation, from having online and evening options to the ease of onboarding. “Part of what made the Penn Alumni Program attractive is that it’s so easy to get into it. The application process is really straightforward for alumni,” she says.

“I really enjoy it and I think I’ve learned a lot,” Francesca concludes. She encourages fellow alumni to take advantage of the resources and options available to them. “Don’t be afraid to try new things and explore, even in a field that you wouldn’t normally have taken a course in,” she advises. “And if you are working professionally and don’t have all the time you would like to dedicate to a course, you can audit or take it pass/fail.”

In 2023, Francesca was accepted to the John F. Kennedy School of Government at Harvard University for a PhD in public policy.