Hello! I am an applied researcher at the intersection of AI, economics, and policy, with experience in experimentation, causal inference, data science, machine learning (LLMs), and reproducibility across industry, academia, government, and international organizations. I am currently a Technology and Security Policy Fellow at RAND, where I work on the science of evaluations, international interoperability, and EU AI policy. I have launched and managed large-scale research projects and collaborated closely with policymakers (i.e. Lithuania, Peru, Paraguay, Slovakia), academic researchers, and engineering/product/data teams to generate meaningful evidence for decision-making. I have lived and worked across five continents and am passionate about promoting AI safety, societal resilience, and sustainable development on a global scale.
Previously I:
- worked as a data scientist at Condé Nast, contributing to LLMs, machine learning models, and experimentation.;<>
- co-designed and -implemented a $2.5M experimental research portfolio on organizations, incentives, and governance with The World Bank, a top 10 economic research institution;
- contributed to DIME's reproducible research agenda, including the DIME Wiki and reproducibility checks.
- contributed to a research initiative studying hierarchy and oversight in Paraguay with researchers from UC Berkeley and University of Wisconsin;
- managed large-scale fieldwork and data collection in Peru with Innovations for Poverty Action and researchers at UC Berkeley and Princeton; and
- designed, ran, and analyzed experiments on biases in recruitment and hiring with the Mind, Behavior, and Development Unit.
I studied Economics at the University of Wisconsin and Barcelona School of Economics.
I am on LinkedIn, GitHub, and Google Scholar. Feel free to get in touch at patriciarosepaskov at gmail dot com.
