Nana Yaw Mante-Asare

Key Skills

Software

V7 Labs

Encord

Top Subject Matter

Geospatial Data Annotation for AI and Logistics

Geospatial AI and Infrastructure Planning

Geospatial Annotation for UAV Routing AI

Top Data Types

Image

Video

Geospatial Tiled Imagery

Top Task Types

Polygon

Segmentation

Bounding Box

Freelancer Overview

Lead – GIS Operations & Data Annotation. Brings 4+ years of professional experience across complex professional workflows, research, and quality-focused execution. Core strengths include V7 Labs. Education includes Bachelor of Science, University of Mines and Technology (2017). AI-training focus includes data types such as Geospatial and Tiled Imagery and labeling workflows including Polygon, Segmentation, and Bounding Box.

Labeling Experience

Lead – GIS Operations & Data Annotation

V7 LabsImagePolygon

Led a 19-person team to manage full-cycle geospatial data annotation for UAV imagery and satellite data. Developed and enforced consistent annotation schemas for object detection, flight-path polygons, and obstacle boundaries used for AI-driven logistics systems. Implemented robust QA/QC measures to maintain high labeling quality supporting ML model training. • Supervised pipeline delivering annotated data across 7 countries • Defined multi-country standardized schema for annotation • Ensured data integrity for operational AI systems • Liaised with leadership to report data quality metrics

Led a 19-person team to manage full-cycle geospatial data annotation for UAV imagery and satellite data. Developed and enforced consistent annotation schemas for object detection, flight-path polygons, and obstacle boundaries used for AI-driven logistics systems. Implemented robust QA/QC measures to maintain high labeling quality supporting ML model training. • Supervised pipeline delivering annotated data across 7 countries • Defined multi-country standardized schema for annotation • Ensured data integrity for operational AI systems • Liaised with leadership to report data quality metrics

2024 - Present

GIS Specialist – Location Engineering & Data Annotation

V7 LabsSegmentation

Used V7 Labs to annotate UAV and satellite imagery for spatial AI model development in logistics and infrastructure. Performed advanced labeling including semantic segmentation, polygons, and coverage mapping for site suitability analysis. Maintained annotated datasets with a focus on accuracy, supporting business-critical spatial analysis. • Delivered accurate labeled datasets for infrastructure planning • Built geospatial annotation workflows and reporting dashboards • Communicated progress and quality to technical stakeholders • Supported downstream AI application development

Used V7 Labs to annotate UAV and satellite imagery for spatial AI model development in logistics and infrastructure. Performed advanced labeling including semantic segmentation, polygons, and coverage mapping for site suitability analysis. Maintained annotated datasets with a focus on accuracy, supporting business-critical spatial analysis. • Delivered accurate labeled datasets for infrastructure planning • Built geospatial annotation workflows and reporting dashboards • Communicated progress and quality to technical stakeholders • Supported downstream AI application development

2023 - 2024

GIS Technician – Spatial Data & Image Annotation

V7 LabsBounding Box

Processed UAV and satellite imagery into DSMs, orthomosaics, and point clouds, and annotated outputs for AI route planning. Applied bounding boxes, polygons, and obstacle labels to geospatial data, ensuring reliable input for logistics automation. Executed QA/QC and verified label fidelity against ground truth datasets. • Produced annotated data supporting reliable flight corridors • Enabled data-driven delivery site deployment • Validated geospatial annotation accuracy for operational use • Supported scaling annotation production for business growth

Processed UAV and satellite imagery into DSMs, orthomosaics, and point clouds, and annotated outputs for AI route planning. Applied bounding boxes, polygons, and obstacle labels to geospatial data, ensuring reliable input for logistics automation. Executed QA/QC and verified label fidelity against ground truth datasets. • Produced annotated data supporting reliable flight corridors • Enabled data-driven delivery site deployment • Validated geospatial annotation accuracy for operational use • Supported scaling annotation production for business growth

2022 - 2023

Education

Work History