Map & Location Data Analyst
Alignerr · Remote · Research / analysis
Map & Location Data Analyst is an open role at Alignerr, available remotely, with pay listed as $40–$120/hr.
Applications open on Alignerr’s own site. How we make money.
At a glance
- Pay
- $40–$120/hrStated by Alignerr
- Location
- Remote
- Work type
- Research / analysis
- Listed
- Since Oct 4, last confirmed Oct 24
How the pay compares
Higher than 75% of the 174 distinct hourly rates advertised for Research / analysis 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
“Map & Location Data Analyst (AI Training) About the Role What if knowing your city — its streets, hidden shortcuts, local landmarks, and neighborhood quirks — could directly improve the AI tools that millions of people rely on every day to find their way?”
Show the full listing
Map & Location Data Analyst (AI Training) About the Role What if knowing your city — its streets, hidden shortcuts, local landmarks, and neighborhood quirks — could directly improve the AI tools that millions of people rely on every day to find their way? We're looking for Map & Location Data Analysts to help verify and improve AI-generated geographic data. You'll put your real-world local knowledge to work, catching the errors and outdated information that algorithms simply can't detect on their own. This is a fully remote, flexible contract role open to anyone with a sharp eye for detail and familiarity with their local area. No GIS, geography degree, or technical background required. Organization : Alignerr Type : Hourly Contract Location : Remote Commitment : 10–40 hours/week What You'll Do Verify AI-generated addresses, place names, and geographic data for accuracy and completeness Evaluate the quality of location-based search results and recommendations Identify and flag incorrect, outdated, or misleading location information Apply your regional knowledge to provide local context and corrections Work through structured, task-based assignments using maps and web-based location tools Document findings clearly and consistently using provided evaluation frameworks Who You Are Familiar with your local area — streets, landmarks, businesses, and neighborhoods Naturally detail-oriented with a consistent, systematic approach to spotting errors Comfortable using digital maps and web-based tools Strong written communication skills Self-motivated and reliable when working independently No GIS, cartography, or geography experience required Nice to Have Experience with mapping platforms such as Google Maps, Apple Maps, or OpenStreetMap Background in local journalism, delivery, tourism, or any role requiring deep geographic familiarity Interest in AI, data quality, or geospatial technology Why Join Us Work on cutting-edge AI projects alongside leading research labs Fully rem
About Alignerr: part of Labelbox. See the full profile →
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Frequently asked questions
How do I apply for the Map & Location Data Analyst 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 Map & Location Data Analyst role at Alignerr remote?
Yes - Alignerr lists this role as remote.
What does the Map & Location Data Analyst role at Alignerr pay?
Alignerr lists this role's pay as $40–$120/hr, quoted from the listing rather than estimated.
What kind of work is Map & Location Data Analyst?
Research / analysis. 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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