Map & Location Data Analyst
Job Description
Our world is increasingly interconnected, and precise location intelligence is critical for everything from logistics to navigation. Your expertise will be vital in teaching AI to interpret, analyze, and generate highly accurate geographic data, powering the next generation of spatial applications.
As a Map & Location Data Analyst, you will be at the forefront of refining AI's understanding of our physical world. You'll evaluate and create training data for geographic information systems (GIS), mapping services, and location-based intelligence, ensuring AI can navigate and understand spatial relationships with unparalleled accuracy.
Key Responsibilities
Evaluate and validate geographic features, points of interest (POIs), and transportation networks on digital maps.
Evaluate AI-generated location data for accuracy, completeness, and consistency against real-world ground truth.
Create detailed descriptions of spatial relationships, topological data, and geocoding information.
Identify and correct errors in AI's interpretation of satellite imagery, street-level views, and cadastral data.
Develop structured training data for specific use cases, such as routing optimization, urban planning, or environmental mapping.
Provide feedback on AI's ability to handle ambiguous or dynamic location information, like construction zones or temporary closures.
Ideal Qualifications
3• years of experience in GIS, Cartography, Geoinformatics, or Location Data Analysis.
Proficiency with GIS software (e.g., ArcGIS, QGIS) and mapping platforms (e.g., Google Maps API, OpenStreetMap).
Strong understanding of spatial data formats (e.g., GeoJSON, KML, Shapefile) and coordinate systems.
Experience with data evaluation, quality control, and validation of geographic information.
Excellent attention to detail and an ability to interpret complex spatial data accurately.
Familiarity with remote sensing, GPS technologies, and location-based services.
Project Timeline
Start Date: Immediate
Duration: Ongoing, task-based
• Commitment: Flexible, 10-20 hours/week
Chart the course for AI's spatial intelligence!