Job Description

Posting Summary
Serve as the AI/ML Ecosystem Data Analyst within the USGS Research Cooperative Unit at UVM,and in collaboration with the Spatial Analysis Lab (SAL). The primary role of this position is to analyze ecological data and design, build, and operationalize AI/ML workflows that collect, process, and derive insight from heterogeneous data sources, including wildlife imagery, bioacoustics recordings, geospatial and remotely sensed data, sensor networks, and field observations. Develop, train, evaluate, and deploy AI/ML models for mapping, classification, and detection of wildlife and other features, and build the data pipelines, databases, and R Shiny or comparable interfaces that make results reproducible, maintainable, and accessible to researchers, partners, and the public. Support the AI/ML branch of RSENR within the Cooperative Unit and SAL, contribute to ecosystem monitoring efforts, and help oversee the Alliance for Monitoring Biodiversity and Ecosystems Remotely (AMBER) program. Work under the direction of the USGS Research Cooperative Unit Leader and collaborate with the SAL Director, RSENR, and other partners on grant writing, business development, and research initiatives, while independently pursuing outside funding opportunities. Partner with geospatial analysts and the development team lead on research and development of new AI/ML methods and models
Minimum Qualifications (or equivalent combination of education and experience)
- PhD in Computer Science, Wildlife Biology, Ecology, Data Science, Bioinformatics, or a closely related discipline, and four years related professional experience.
- Demonstrated expertise in data science, machine learning, and AI applications.
- Strong proficiency in relational database design and management, including stand-alone programs such as SQLite and served databases such as SQL or Postgres.
- Experience with APIs, web services, Power Automate, Teams, and Sharepoint for workflow integration.
- Strong record of interdisciplinary collaboration and scientific productivity.
- Experience managing complex technical or research projects, including grant writing.
- Experience with cloud-native infrastructure and scalable AI workflows, focused primarily on the R and Python coding languages.
- Substantial experience in working with the public and agency monitoring partners.

Desirable Qualifications
- Postdoctoral experience preferred
- High proficiency in public outreach and instruction desired
- Supervisory or personnel management experience desired
Anticipated Pay Range $80,000 - $95,000
Other Information
Special Conditions A probationary period may be required, Contingent on continued funding, Occasional evening and/or weekends required (if non-exempt position, may result in overtime), Travel to and from worksites required, This position is eligible for a hybrid schedule with an option to split time between campus and elsewhere, in accordance with the university telecommuting policy, Background Check required for this position