Copy of Geospatial Research & Analysis Experts

Description

This opportunity is ideal for professionals and researchers with strong geospatial knowledge and experience in GIS, spatial analysis, and geospatial data tools. Candidates should be comfortable reviewing open-ended questions, developing analytical approaches, and explaining their methods clearly.

Depending on their assessment results and the client's requirements, selected candidates may be assigned to either an Operator or Quality Assurance (QA) role.

What You'll Do:

• Review geospatial queries and identify unclear terms, missing information, and other gaps that may affect the analysis.
• Suggest clarifications and reasonable assumptions to turn complex questions into well-defined geospatial problems.
• Develop detailed, step-by-step workflows for geospatial analysis.
• Identify appropriate data sources, tools, analytical methods, and validation steps.
• Define expected deliverables, such as maps, reports, and other outputs.
• Apply geospatial knowledge to real-world scenarios, such as crisis response, damage assessment, agriculture, site selection, market expansion, supply chain analysis, and forecasting.
• For QA assignments, review completed work, check its quality, and provide feedback based on project guidelines.

Requirements

• Bachelor's, Master's, or PhD degree in a relevant field, such as:

  • Geographic Information Science (GIS) or Geospatial Science.

  • Geography with a focus on GIS or spatial analysis.

  • Geomatics.

  • Remote Sensing or Earth Observation.

  • Geospatial Engineering or a closely related discipline.

• Strong geospatial expertise gained through professional experience, academic research, or both.
• Experience working with geospatial data and tools such as QGIS, ArcGIS, GeoPandas, Google Earth Engine, or Google Earth.
• Experience applying geospatial analysis to real-world problems or research projects.
• Ability to evaluate complex questions, identify missing information, and explain analytical assumptions and methods.
• Strong written communication skills in English.
• Excellent attention to detail and ability to follow project guidelines.

Nice to Haves:

• Experience working as a GIS Analyst, Geospatial Engineer, GIS Data Analyst, or Geospatial Researcher.
• Experience with crisis response, damage assessment, agriculture, site selection, market expansion, supply chain analysis, or forecasting.
• Additional coursework or training in geospatial frameworks, tools, and libraries.
• Previous experience with AI training, data annotation, or quality assurance projects.

Additional Information

• Fully remote freelance opportunity.
• Flexible, project-based work that can be completed remotely.
• Work is expected to begin immediately, with no projected end date.
• Work volume and availability may vary depending on project needs.
• Operator / Task Production Rate: $35 per hour.
• Quality Assurance (QA) Rate: $40 per hour.
• The client's assessment results will determine eligibility and placement in either an Operator or QA role.

Important Notes:

• All project work, onboarding, and payments will be handled directly through the client's platform (Invisible). Freelancers will not receive contract offers or payments through Upwork.
• Completing the assessment does not guarantee selection. The client will make all final decisions regarding eligibility and placement.
• An active task pool is required before work can begin, so task availability may vary.
• Information received from or about the client is confidential under Section 15 of the Upwork User Agreement and must not be shared with unauthorized parties.
• This is an Upwork-approved off-platform opportunity. Participating in this project does not violate Upwork's non-circumvention terms.

An enterprise client is seeking experienced Geospatial Research & Analysis Experts to support an AI-training project focused on developing expert-level analytical workflows.

The selected freelancers will help train an AI assistant by reviewing complex geospatial questions, identifying missing information, making reasonable assumptions, and creating detailed workflows for solving real-world spatial problems.