In April 2023, New Jersey Governor Phil Murphy signed an executive order which revised the requirements for a slew of state government job opportunities – changing an emphasis on a four-year college degree to prioritize work experience instead. Kim Kreiss, who recently graduated with her master’s from Princeton University’s School of Public and International Affairs (SPIA) wanted to know: how would the order improve labor market outcomes for non-college degree holders, if at all? 

“Skill-based hiring is in theory a promising policy idea, but in practice, potentially difficult to implement,” said Kreiss. “Seeing how it impacts the population of interest is really good information to have.” 

Kreiss decided to make the question the center of the research project she completed as a part of the requirement to receive a graduate certificate in Statistics and Machine Learning, which she pursued alongside her master’s in public affairs (MPA).

For the project, Kreiss acquired datasets provided by a software company which contained information scraped from LinkedIn and other job posting websites. Using statistical methods, she analyzed the datasets to determine whether there was an increase in people without college degrees hired into government roles after the order went into effect.

Ultimately, Kreiss’ project didn’t show any significant effect on the number of people without four-year degrees in state government jobs. But, that doesn’t mean she’s writing off the project – or skills-based hiring as an effective policy intervention. Government jobs only make up a small share of the labor market, and it takes time for the effects of such an executive order to be seen, particularly in hiring. “I’d like to extend the analysis out longer,” said Kreiss. “Since it’s been such a short time since the order went into effect, there hasn't been time for outcomes to show up in other variables, like wages.”

Before graduate school, Kreiss worked first as a research assistant, then a data scientist at the Federal Reserve Board. While there, she worked on projects that used data and research to inform Federal Reserve policy. “I really liked doing that work,” said Kreiss. “I wanted to improve my skills in that realm.” 

Pairing statistics and policy

By the time she arrived at Princeton to start her MPA, Kreiss was already prepared to begin an SML certificate to compliment her degree. “Before I got to campus, the Center for Statistics and Machine Learning was definitely on my radar,” said Kreiss.

Of all her experiences as a student in the SML certificate program, Kreiss said the one that stood out most was the time she took part in the Graduate Research Seminar, during which students share their scholarly research with their classmates. “The seminar really fosters community, especially across departments with people you otherwise wouldn’t have interacted with,” said Kreiss.

Kreiss said she believes the SML certificate is a “great” way to pair policy analysis and SPIA courses with more advanced statistical topics and machine learning. Early on in her career, while with the Federal Reserve Board, Kreiss witnessed the importance of and emphasis on data-driven policy and evidence-based policy decisions – something that continues to increase in today’s world. 

“With advancements in digital infrastructure, machine learning, and computational capabilities, we now have access to vast amounts of high quality and real time data,” said Kreiss. “Being able to have the tools and methods to understand and leverage these data to inform policy is really valuable.”