Natural Resource Conservation Scientist
Alignerr · United States · 2 days ago
RemoteRemoteOTHRContract
About The Role
We're looking for experienced natural resource conservation scientists to help shape the next generation of AI. Your scientific expertise will directly influence how AI systems understand, reason about, and communicate environmental science — from ecosystem management to biodiversity conservation. This is a fully remote, flexible contract opportunity where your real-world knowledge makes a measurable difference in AI quality.
What You'll Do
- Review conservation science questions, scenarios, and case studies used in AI training datasets
- Evaluate the scientific accuracy of AI-generated content covering land use, ecosystems, soil science, hydrology, and biodiversity
- Assess whether AI recommendations reflect real-world conservation best practices and land management standards
- Identify errors, gaps, or misleading reasoning in AI-generated environmental science outputs
- Provide clear, structured feedback to improve AI scientific reasoning and response quality
- Work independently and asynchronously to complete task-based assignments on your schedule
Who You Are
- 3+ years of professional experience in natural resource conservation, land management, or environmental science
- Strong foundational knowledge of ecosystems, conservation principles, and applied land management
- Able to critically evaluate scientific reasoning and identify flawed or impractical recommendations
- Comfortable reading and providing detailed written feedback on structured content
- Self-motivated and reliable — you can manage your own workflow without close supervision
- No prior AI experience required
Nice to Have
- Master's degree or PhD in Natural Resources, Environmental Science, Ecology, or a related field
- Hands-on fieldwork or applied conservation project experience
- Familiarity with conservation policy frameworks, land management regulations, or ecosystem restoration
- Prior experience with content review, technical writing, or evaluation workflows