Summary
Jinsu Elhance is a geospatial data scientist with eight years of cross-disciplinary experience applying machine learning and remote sensing to conservation and environmental justice. Currently at SPUN, he designs maps and scientific workflows to protect mycorrhizal networks while previously building real-time hydrology monitoring and sensor networks for the Jack and Laura Dangermond Preserve at The Nature Conservancy. He has developed regional mangrove classification and degradation time-series models using only freely accessible data and tools to support Blue Carbon initiatives across East Africa, building on his MSc thesis on species discrimination along Kenya’s coastline. Equally comfortable in the field deploying sensors and cameras as he is coding reproducible pipelines and classification models, Jinsu bridges community-led conservation with scalable data science. His background spans academic research in reinforcement learning for conservation, procurement-focused classification systems for government, and full-stack product development—reflecting a rare blend of ecological domain knowledge, policy-facing impact, and production engineering. Based in Oakland, he combines technical rigor with a clear focus on making environmental data accessible to diverse stakeholders.
8 years of coding experience
6 years of employment as a software developer
Bachelor of Arts - BA, Computer Science, Bachelor of Arts - BA, Computer Science at University of California, Berkeley
International Baccalaureate, International Baccalaureate at UWC Atlantic College
Master of Science - MS, Climate Change: Environmental Science and Policy, Master of Science - MS, Climate Change: Environmental Science and Policy at King's College London
Spanish, English