Hillary N.

Key Skills

Software

Label Studio

Other

Scale AI

Toloka

Top Subject Matter

Geospatial mapping validation

land cover classification

environmental feature identification

Top Data Types

Image

Video

Geospatial Tiled Imagery

Top Task Types

Data Collection

Segmentation

Classification

Object Detection

Text Generation

Question Answering

Text Summarization

Evaluation/Rating

Fine-tuning

Freelancer Overview

AI Data Labelling Consultant & Senior Geologist — Geotech Engineering Services (AI training data annotation, QA, and val. Brings 9+ years of professional experience across complex professional workflows, research, and quality-focused execution. Core strengths include Label Studio and Other. Education includes Bachelor of Science, University of Maiduguri (2018). AI-training focus includes data types such as Geospatial and Tiled Imagery and labeling workflows including Segmentation and Classification.

Labeling Experience

AI Data Labelling Consultant & Senior Geologist — Geotech Engineering Services (AI training data annotation, QA, and validation)

Label StudioSegmentation

Annotated satellite imagery and aerial photographs for AI/ML training geospatial datasets, including roads, buildings, vegetation, water bodies, geological formations, and land use types. Performed ground-truth validation by comparing automated classifications with field-observed landmarks and correcting misidentified entities. Applied expert geological domain knowledge to ensure accurate, guideline-compliant labeling and consistent annotations across large-scale batches. • Roads and infrastructure tagging • Object/feature identification across urban and rural Nigerian environments • Ground-truth validation and correction of misclassified landmarks • Quality assurance and guideline enforcement for label consistency

2021 - Present

Geologist & Geospatial Data Analyst — Keep Nature Nigeria Limited (imagery interpretation and labeled dataset preparation)

OtherClassification

Interpreted satellite imagery and aerial photographs to identify and label geological features, land cover types, and environmental indicators for geospatial documentation. Collected and structured field geospatial data to support annotated datasets suitable for downstream spatial AI workflows. Ensured contextual accuracy by applying knowledge of local Nigerian terrain and landscape patterns to location-based annotations. • Geological feature identification and labeling • Land cover/environmental indicator annotation • Structuring field-to-map data for labeled datasets • Support for subsurface-related spatial documentation workflows

2018 - 2021

Education

Work History