Ecological AI/ML Data Analyst

University of Vermont; Burlington (VT); Hybrid; USD 80,000 - 95,000; Full time

Job summary

The University of Vermont invites applications for an AI/ML Ecosystem Data Analyst in Burlington, VT. You will analyze ecological data, design and operationalize AI/ML workflows, and build data pipelines and interfaces to make results reproducible and accessible to researchers and the public.

You will train, evaluate, and deploy models for mapping and detection, collaborate with the Spatial Analysis Lab and RSENR, assist with grant writing, and seek outside funding opportunities, including

Qualifications

• PhD in a related discipline with four years of relevant experience.
• Expertise in data science, machine learning, and AI applications.
• Strong proficiency with relational databases (SQLite, PostgreSQL).
• Experience with APIs, web services, Power Automate, Teams, and Sharepoint for workflow integration.
• Demonstrated interdisciplinary collaboration and scientific productivity.

Responsibilities

• Analyze ecological data and design, build, and operationalize AI/ML workflows.
• Develop, train, evaluate, and deploy AI/ML models for mapping, classification, and detection.
• Build data pipelines, databases, and interfaces (R Shiny or comparable).
• Collaborate with SAL, RSENR, and partners on grant writing and research initiatives.
• Pursue outside funding opportunities and partnerships with agencies.

Skills

Data science

Machine learning

Relational databases

Python

R

Cloud-native infrastructure

Grant writing

Education

PhD in Computer Science

PhD in Ecology

PhD in Wildlife Biology

PhD in Data Science

PhD in Bioinformatics

Tools

SQLite

PostgreSQL

APIs/web services

Power Automate

SharePoint

SQL

Job description

The University of Vermont invites applications for an AI/ML Ecosystem Data Analyst in Burlington, VT. You will analyze ecological data, design and operationalize AI/ML workflows, and build data pipelines and interfaces to make results reproducible and accessible to researchers and the public.

You will train, evaluate, and deploy models for mapping and detection, collaborate with the Spatial Analysis Lab and RSENR, assist with grant writing, and seek outside funding opportunities, including