Jennifer Pearl is the director of the Science & Technology Policy Fellowships (STPF) program at the American Association for the Advancement of Science (AAAS). Prior to coming to AAAS, Pearl was at the National Science Foundation for 12 years, where she served in the Division of Mathematical Sciences and Office of International Science & Engineering. She was a AAAS S&T Policy Fellow in 2002–2003 and has a PhD in mathematics.
While the world is in disarray due to the COVID-19 pandemic and people are waiting to see where everything lands, life continues onward. And your career is part of that.
The federal sector in the United States continues to show great appreciation for technical expertise in places both expected and unexpected. The President’s Council of Advisors on Science and Technology has been reconstituted. The Government Accountability Office is beefing up science and technology (S&T) efforts. And the National Academy of Public Administration released a report that recommends enhancing existing S&T resource support in Congress.
Specifically, offices across the federal government show high demand for science and engineering professionals with expertise in data. Run by the American Association for the Advancement of Science (AAAS), the Science & Technology Policy Fellowships (STPF) program matches statisticians, mathematicians, other scientists, and engineers with agencies where the need is easily apparent—the Bureau of Labor Statistics or US Census Bureau, for example. But fellows are also found helping drive data-intensive efforts at agencies where the need may not be as obvious, such as the Department of State and Department of Agriculture.
The STPF program receives requests from executive branch agencies for fellows at a pace well beyond what it can recruit—about a third of these unmet requests were for fellows skilled in data science. And fellowship finalists who have backgrounds in statistics, mathematics, and computer science often land more than double the number of interviews as other finalists.
Jiayang Sun (STPF class of 2019–2020) is chair of the department of statistics at George Mason University. She was among the first science policy fellows to be sponsored by a consortium of organizations: ASA/ACM/AMS/IMS/MAA/SIAM. Placed at the US Department of Agriculture, she helped develop and support the Partnerships for Data Innovation initiative to meet challenges in feeding the world sustainably. She came to the fellowship with the aim of building networks and find research opportunities of national relevance, “promot[ing] proper use of statistics for evidence-based research, and contribut[ing] to making a better society.”
Samantha Tyner (STPF class of 2019–2020) was the Bureau of Labor Statistics’ (BLS) first STPF fellow. She just completed her fellowship as a statistician in the BLS Office of Survey Methods Research, where she focused on interactive data visualization, text mining, and effective communication to wider audiences.
After the fellowship, STPF fellows move on—often in leadership roles—to every sector; some remain in government. When the Big Data Regional Innovation Hubs were established by the National Science Foundation in 2015, four STPF alumni were at the helm of three of the four hubs.
The yearlong STPF fellowship runs from September through August and includes close to 300 fellows who represent a broad range of backgrounds, disciplines, and career stages. Fellows broaden their career paths while engaging with policymakers and thought leaders. After their fellowship, fellows become members of a strong corps of 3,400+ alumni—policy-savvy STEM leaders in academia, government, industry, and the nonprofit arena.
Cautionary tales abound about what can happen when data is misused, but the right use of data by the government can help identify and solve every type of policy problem, from health to housing. The key to improving the government’s ability to collect and analyze data to inform decision-making—as well as implement the right data policies to protect the public—is to have individuals at the table who are well-versed in areas including statistics, analytics, and machine learning.
Statistics expertise applied toward the public good is in demand and in our best interest. The deadline to apply is November 1.
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