Natural Resource Conservation Scientist
Alignerr · Remote · Data annotation / labeling
Natural Resource Conservation Scientist is an open role at Alignerr, available remotely, with pay listed as $30–$55/hr.
Applications open on Alignerr’s own site. How we make money.
At a glance
- Pay
- $30–$55/hrStated by Alignerr
- Location
- Remote
- Work type
- Data annotation / labeling
- Field
- Science / STEM
- Listed
- Since Oct 4, last confirmed Oct 23
How the pay compares
Higher than 22% of the 106 distinct hourly rates advertised for Science / STEM roles right now. Hourly USD, top of each advertised range, one count per distinct rate. Same method as the Pay Index.
From Alignerr’s listing
“Natural Resource Conservation Scientist (AI Training) About the Role We're looking for experienced natural resource conservation scientists to help shape how AI understands environmental science, land management, and conservation decision-making.”
Show the full listing
Natural Resource Conservation Scientist (AI Training) About the Role We're looking for experienced natural resource conservation scientists to help shape how AI understands environmental science, land management, and conservation decision-making. Your field knowledge and scientific expertise will directly influence the accuracy and reliability of AI systems tackling some of the most important environmental challenges of our time. Organization : Alignerr Type : Hourly Contract Location : Remote Commitment : Flexible, asynchronous What You'll Do Review and evaluate conservation science questions and scenarios used in AI training datasets Assess the scientific accuracy of AI-generated content covering land use, ecosystems, soil, water, and biodiversity Determine whether AI-generated recommendations reflect real-world conservation practices and sound scientific reasoning Provide clear, structured feedback to improve the quality and reliability of AI outputs Work independently and asynchronously to meet project milestones on your own schedule Who You Are 3+ years of professional experience in natural resource conservation, land management, or environmental science Strong working knowledge of ecosystems, conservation principles, and applied land stewardship Able to critically evaluate scientific reasoning and practical recommendations with clarity and precision Comfortable reviewing structured written content and delivering detailed, actionable feedback Self-motivated and reliable with the ability to manage your own workload remotely 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 AI systems, content evaluation workflows, or data annotation Why Join Us Work on cutting-edge AI projects with top research labs making a real environmental impact Fully remote and flexible — contribute on your own schedule from anywhere Freelance perks: aut
About Alignerr: part of Labelbox. See the full profile →
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Frequently asked questions
How do I apply for the Natural Resource Conservation Scientist role at Alignerr?
Applications go through Alignerr's own portal - HumanSourcer links to the listing and never collects applications or handles hiring. Alignerr's access model is "Open / self-serve" (Open roles / applications). This listing was first seen here on October 4, 2026 and was still live at the last check.
Is the Natural Resource Conservation Scientist role at Alignerr remote?
Yes - Alignerr lists this role as remote.
What does the Natural Resource Conservation Scientist role at Alignerr pay?
Alignerr lists this role's pay as $30–$55/hr, quoted from the listing rather than estimated.
What kind of work is Natural Resource Conservation Scientist?
Data annotation / labeling. AI training, evaluation, coding, writing and specialist review
Is Alignerr a legitimate AI-training platform?
Labelbox expert network - and that relationship is rated "Confirmed" here because it can be checked against labelbox.com rather than taken on Alignerr's word. Confidence describes how well the ownership is evidenced. It is not a rating of how the platform treats the people who work for it, which no public source covers reliably.
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