Summary
Jennie Sun is a data scientist and technical lead with eight years of interdisciplinary experience applying statistical methods, BI tools, and machine learning to drive measurable business and environmental impact. Currently a Duke Energy Initiative Project Fellow and MIDS graduate student, she builds production-ready pipelines and 3D-augmented remote sensing datasets for energy infrastructure while guiding student teams on best practices and experimental design. Her background spans industry and research—from scaling CNN-based face-detection pipelines at Nike (0.96 validation accuracy) to improving recycling KPIs via customer-facing dashboards—demonstrating fluency across ML, data engineering, and visualization. Jennie combines domain experience in environmental science and public health with pragmatic optimization and cost-benefit thinking to turn complex data into actionable strategies. Colleagues value her for bridging technical depth with mentorship and for translating novel analytics into operational improvements that scale.
8 years of coding experience
2 years of employment as a software developer
Liberal Arts and Sciences, Liberal Arts and Sciences at Oxford College of Emory University
MIDS - Master in Interdisciplinary Data Science, MIDS - Master in Interdisciplinary Data Science at Duke University
Bachelor’s Degree, Environmental Science & Economics, 3.5, Bachelor’s Degree, Environmental Science & Economics, 3.5 at Emory University
London School of Economics and Political Science
English, French, Chinese