Timothy Divoll is a PhD-level senior data scientist based in Greater Boston with nine years of experience applying machine learning and statistical modeling to environmental consulting, university research, and operational decision-making. He builds end-to-end solutions—from scraping and feature engineering to model deployment (Streamlit/Heroku) and object-detection/image-classification tools—to improve field survey efficiency and predict outcomes like nurse turnover. His background in spatial and molecular ecology of bats informs a practical blend of bioacoustics, NGS bioinformatics, GIS, and telemetry-derived spatial analyses, enabling cross-disciplinary problem solving. Timothy pairs strong field experience managing remote teams and grant-funded studies with production-facing data science, mentoring interns and deploying models as apps for nontechnical stakeholders. Notably, he translated ecological rigor into healthcare analytics, engineering features from Glassdoor and public hospital data to produce actionable churn predictions that quantified potential savings per nurse.
9 years of coding experience
12 years of employment as a software developer
BS, Biology, 3.5, BS, Biology, 3.5 at Worcester State College
Doctor of Philosophy - PhD, Ecology, 3.5, Doctor of Philosophy - PhD, Ecology, 3.5 at Indiana State University
MS, Biology, 3.4, MS, Biology, 3.4 at University of Southern Maine
Contributions:59 reviews, 123 commits, 43 PRs in 6 months
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