Ricardo Masini, a newly appointed lecturer for Princeton University’s Center for Statistics and Machine Learning (CSML), brings an eclectic background to his job, including stints as a systems engineer and business consultant. But the one he treasures the most is educator.
Masini joined CSML this January and is currently teaching CSML’s flagship undergraduate data science course, SML 201: Introduction to Data Science this semester. Before joining CSML, he was a visiting professor at the Department of Operations Research and Financial Engineering (ORFE) beginning in 2019.
“I am happy to join the team at CSML and that I get to impart my love of data science and machine learning to undergraduates. Teaching data science to people is something I am passionate about,” he said. “Data science is increasingly becoming an important part of so many aspects of our world. So, it’s essential that we provide data science education, whether for people who want to become data scientists or students who want to know it as part of a broad-based general education.”
“We are pleased that Ricardo has joined CSML, during what is a particularly tough time to be an educator due to the pandemic,” said Peter Ramadge, CSML director. “He brings an interesting, varied background that should add richness to our data science community.”
Masini, who is originally from Brazil, did not envision working in academia or teaching data science when he was younger. He studied aeronautical engineering at University of Sao Paulo, where he earned his bachelor’s degree in 2002. He entered the work force and was employed in Brazil’s space industry as a systems engineer for Embraer, an aerospace company that builds commercial, military, executive and agricultural aircraft and provides aeronautical services. He then joined Airbus in Bristol, United Kingdom as a lead system engineer before deciding to get his MBA in finance at the business school, INSEAD, based in Fontainebleau, France and Singapore.
On why he left the aeronautics industry, Masini said, “I wanted to stretch my intellectual horizons and learn something new. I wanted to study more.”
After earning his MBA, he worked as an associate consultant at McKinsey & Company in Brazil. He worked on various projects, from mergers and acquisitions to marketing. But his stint in the corporate world made him realize that what he really wanted to do was go back to school, go into academic, and study economics and statistics.
“When I was my MBA, that was the first time I saw economics as a field and I saw a potential niche. I began to really like econometrics, which is kind of a mix between statistics and economics,” he said.
Masini went to the London School of Economics where he earned his master’s degree in economics in 2011. The next year, he then moved back to Brazil and enrolled for a doctoral degree in economics at Pontifical Catholic University of Rio de Janeiro. It was during this time that he developed an interest in machine learning, data science and counterfactual analysis which formed the basis of his thesis, “Contributions to the Econometrics of Counterfactual.”
Counterfactual analysis asks how the results of an intervention can be compared to results that might arise under alternative actions. Masini’s thesis explored a new method to conduct counterfactual analysis by using advanced computational modeling.
During his doctoral years, from 2012 to 2016, Masini taught classes on futures and derivatives and fixed income assets. After getting his doctoral degree, he was a lecturer at EESP-FGV, a major economics educational institution in Sao Paolo, Brazil. He taught classes on statistics, probability and time series analysis.
He then assumed a position as visiting professor at ORFE, where he taught classes on analysis of big data, fundamentals of statistics, and regression and applied time series.
“It’s been a journey, from being in aeronautical engineering to working as a business consultant and to academia,” said Masini. “But I enjoy teaching. It energizes me. It gets me pumped up.”
“I especially love it when students have an epiphany and understand a complex idea,” he added. “It’s a great feeling when that happens.”