AI/ML Ecosystem Data Analyst

University of Vermont; New Jersey; Hybrid; USD 80,000 - 95,000; Full time

Benefits offered by this job

Hybrid schedule

Job summary

University of Vermont is seeking an AI/ML Ecosystem Data Analyst to design and implement AI/ML workflows across diverse ecological data sources, including wildlife imagery and geospatial data. The role emphasizes building reproducible pipelines and interfaces for researchers and the public.

You will work with SAL, RSENR, and partners to pursue funding, develop novel AI/ML methods, and advance ecosystem monitoring through AMBER and related initiatives.

Qualifications

• 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 SQLite and 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.

Responsibilities

• Analyze ecological data and design, build, and operationalize AI/ML workflows collecting and processing heterogeneous data sources.
• Develop, train, evaluate, and deploy AI/ML models for mapping, classification, and detection of wildlife and features.
• Build data pipelines, databases, and interfaces (R Shiny or similar) for reproducible, maintainable results.
• Collaborate with SAL and RSENR, pursue outside funding opportunities, and support AMBER program oversight.
• Partner with geospatial analysts and development leads on R&D of new AI/ML methods and models.

Skills

Data science

Machine learning

AI applications

Relational databases

APIs

Power Automate

Teams

SharePoint

R

Python

Cloud-native infra

Education

PhD in Computer Science, Wildlife Biology, Ecology, Data Science, Bioinformatics, or related discipline

Tools

SQLite

PostgreSQL

APIs

Power Automate

Teams

SharePoint

Job description

Position Details

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 FLSA Exempt Union Position Yes, UVMSU

Posting Details

Position will be posted for a minimum of one week, after which it is subject to removal without notice.

Job Location Burlington, Vermont, United States

Job Open Date 08/20/2026

Job Close Date (Jobs close at 11:59 PM EST.) Open Until Filled No

Our Common Ground Statement

The University of Vermont is a welcoming, educationally purposeful community committed to creating an inclusive environment that embraces intellectual diversity and global perspectives. We seek to prepare students to be accountable leaders who will bring to their work a grasp of complexity, effective problem-solving and communication skills, and an enduring commitment to learning and ethical conduct. Members of the University of Vermont community embrace and advance the values of Our Common Ground: Respect, Integrity, Innovation, Openness, Justice, and Responsibility. Staff play a critical role in this effort and the successful candidate will demonstrate a strong commitment to UVM’s mission and advancing Our Common Ground values through the execution of their job duties.

Position Information

Position Title Research Data Analysis PC5 X Posting Number S6267PO Department Rubenstein Sch Env & Nat Res/57000 Position Number 00027971 Percent of Full-Time 1.0 Standard Hours at 1.0 FTE 37.5 Term (months per year) 12

Supplemental Questions

Required fields are indicated with an asterisk (*).

Required Documents

• Resume
• Cover Letter/Letter of Application

Optional Documents

• Other Document (1)