Summary
Morgan Ziegenhorn is a wildlife ecologist and data scientist with eight years of experience applying machine learning, Bayesian modeling, and spatial-temporal analysis to large-scale environmental datasets. Currently a Research Associate in Data Science and Acoustic Ecology, Morgan has led multi-institutional projects monitoring migratory birds and marine mammals, producing peer-reviewed publications and actionable insights for government and conservation partners. Skilled in Python, R, QGIS, and command-line workflows, they combine fieldwork—deploying and maintaining acoustic sensors across remote sites—with rigorous remote-sensing and bioacoustic analysis. Morgan is adept at translating complex technical results into clear visuals and reports for both scientific and non-technical audiences, helping funders and managers make evidence-based decisions. Recognized for community outreach and early-career research excellence, they bring a rare blend of hands-on field experience and advanced algorithm development to conservation challenges. An often-overlooked strength is their track record of coordinating logistics and procurement for Arctic field seasons, ensuring projects run smoothly in extreme conditions.
8 years of coding experience
1 year of employment as a software developer
Bachelor of Arts - BA Ecology Evolution and Organismal Biology, Bachelor of Arts - BA Ecology Evolution and Organismal Biology at University of California, Berkeley
University of California, San Diego