Alumni Profile: Si Cheng, Policy Analytics Credential’24

Si Cheng, PAC’24, joined the Policy Analytics Credential (PAC) program to add quantitative policy analysis skills to her social science background.

“I’m a social science researcher with a thematic focus on environmental history and energy policy,” said Cheng, “and PAC’s curriculum seemed a great start for my data analysis journey. Learning analytics and basic data visualization skills can support and complement my previous academic and professional experiences while also providing transferable skills I can use for exploring other career opportunities.”

Although Cheng applied for the PAC along with the Environmental Economics and Policy Lab (EEPL) program in Beijing in 2024, she first started to look for relevant courses while studying for her MA in Social Sciences at the University of Chicago in 2023. “My thesis analyzed a policy debate on energy security in the United States after the 1973 oil crisis. To better examine how scientists supported their claims about long-term energy demand and energy choices, I needed to build a better understanding of their quantitative modeling methods and the logics behind their data-dense economic calculations.”

Cheng said one benefit of the PAC she hadn’t expected was the breadth of the help and inspiration she received from the Harris community. “The conversations I had with instructors and teaching assistants during office hours really shined a light on how one can enhance their research and thus go further on their overall path. For example, one of our instructors, Jose Macias, showed me how he and his colleagues used R and stats to help them analyze scenarios and summarize findings to produce better international relations recommendations on cybersecurity and national security in the United States.

“Plus,” Cheng added, “hearing how fellow participants planned to use these quantitative analytical tools to help them go further in their careers really inspired me.”

As for the academic components of PAC, Cheng said the online data workshops were especially invaluable. “They really helped me go from knowing nothing on day one to being able to independently think about how to apply the functions and syntax we learn during the week to solve a given problem set.”

However, Cheng said the most gratifying outcome of the program was learning how to use data visualization. “My group and I analyzed crime and housing data in Chicago, and when we were able to generate an interactive visual representation of that data as a multi-layer map, it was exciting! To be able to turn lifeless datapoints into a real, tangible product that showed the correlations between housing, income, and crime that supported further analysis was incredibly rewarding.”

Moving forward, Cheng said she aims to continue expanding her coding skills in Python and SQL. “I’m excited to combine my research capacities and qualitative and quantitative skills. I’m looking forward to getting out of my comfort zone of primarily researching and reading about environmental issues and seeing how I can use my quantitative skills to make a larger impact.”