Geospatial Analyst

The Role 

As a Geospatial Analyst at AiDASH, you will produce high-quality annotated datasets from diverse imagery sources — satellite, LiDAR, aerial, and ground-based panoramic images and videos. Your work will directly feed AI/ML pipelines and client deliverables that protect critical infrastructure. This role demands a sharp eye for detail, comfort working with visual and geospatial data at scale, and fluency with modern AI tools. You won’t just annotate images; you’ll build AI-accelerated workflows that make the entire team faster. 

How You’ll Make an Impact 

• Annotate and label imagery (satellite, LiDAR, aerial, drone, ground-based panoramic photos and videos) to identify, classify, and delineate features such as vegetation, assets, terrain, and infrastructure components 

• Prepare, extract, and organize spatial and non-spatial data based on AI model and customer delivery requirements 

• Review annotated data for patterns, trends, and quality issues using annotation platforms and in-house tools 

• Use AI tools and assistants to accelerate annotation and workflows, auto-generate documentation, and draft reports 

• Perform annotation tasks including object classification, digitization, geo-referencing, and feature creation across multi-source imagery 

• Leverage generative AI tools to build automations or semi-automated annotation pipelines that boost team productivity 

• Collaborate with AI/ML engineers to define annotation guidelines, refine labelling schemas, and ensure datasets meet model training and delivery standards 

• Ensure productivity targets are met with utmost focus on annotation quality, consistency, and adherence to project specifications 

What We’re Looking For 

• 1 to 4 years of work experience in imagery annotation, image analysis, remote sensing, or a related domain 

• Hands-on experience with annotation and labelling platforms; familiarity with GIS software is an added advantage 

• Demonstrated use of generative AI tools(e.g. Claude, ChatGPT) to enhance day-to-day work — whether for analysis, drafting reports, automating repetitive tasks, improving annotation speed, or any other productivity gains 

• Comfortable using Gen AI tools to draft reports, generate annotation guidelines, and summarize analysis outputs with sound judgment 

• Working knowledge of Python or scripting for data processing and automation is preferred; geospatial libraries are a bonus 

• Experience working with satellite imagery, aerial photography, LiDAR point clouds, or video annotation for AI/ML pipelines 

• Ability to learn quickly and develop deep functional knowledge of project specifications, annotation schemas, and quality procedures 

• Strong focus on data quality, annotation accuracy, and consistency across large-scale datasets