Spatial Data Analyst; GIS AI Evaluation

Evaluate AI-generated content about GIS, spatial analysis, and environmental mapping from the United States. This remote, ongoing contract offers flexible scheduling, 20+ hours per week, and up to $125 per hour.

Remote Hourly $125/hr

$125/hr

Compensation

Contract, part-time

Engagement

Remote

Location

Posted

Open to applicants in

United States

This role involves evaluating how well AI systems understand geographic information systems, spatial data analysis, and environmental mapping. You will create domain-specific prompts, review generated responses, and give clear feedback on accuracy, relevance, and technical quality.

The listing is titled Spatial Data Analyst, while the listed duties focus on GIS AI response evaluation. Review these duties and qualifications before applying.

• Create prompts based on GIS, spatial analysis, and environmental mapping workflows.
• Review AI-generated responses for accuracy, relevance, and understanding of spatial data concepts.
• Explain strengths, errors, and ways AI-generated content could improve.
• Use QGIS and related technical tools when assessing domain-specific work.
• Work independently and communicate technical feedback asynchronously.

This is remote, asynchronous, ongoing, project-based contract work. Work is available according to project needs, and the structured schedule is 20+ hours per week.

• Pay:
  Up to $125 per hour.
• Location:
  
  Open to candidates in the United States.
• Language:
  Professional fluency in English.
• Schedule:
  
  Flexible, with 20+ hours per week.
• Experience:
  
  At least one year using QGIS or related technical tools.
• Skills:
  
  Hands-on experience with GIS, spatial data analysis, or environmental mapping.
• Skills:
  
  Ability to write domain-specific prompts and evaluate AI-generated responses.
• Skills:
  
  Strong judgment when assessing GIS tasks and spatial data workflows.
• Helpful background:
  Real-world QGIS experience in spatial analysis or environmental mapping, plus experience giving technical feedback asynchronously.

AI training is the human work behind systems that generate and understand content. Contributors prepare examples, review model responses, and give feedback so AI systems perform better, while people with specialized experience can contribute informed evaluations in their field.