Clement K.

Key Skills

Software

Don't disclose

Top Subject Matter

Geospatial land use mapping

urban classification

and field-survey verification

Top Data Types

Text

Image

Document

Top Task Types

Segmentation

Freelancer Overview

Geospatial Data Annotator & Surveyor (Fieldwork) — spatial semantic segmentation and ground-truth verification (Laikipia. Brings 2+ years of professional experience across complex professional workflows, research, and quality-focused execution. Core strengths include ArcGIS and Don't disclose. Education includes Bachelor of Science, Laikipia University (2025) and Kenya Certificate of Secondary Education (KCSE), Kanyuambora Boys High School (2020). AI-training focus includes data types such as Geospatial, Tiled Imagery, and Text and labeling workflows including Segmentation, Translation, and Localization.

Labeling Experience

AI Safety & Localized Text Evaluator — transaction labeling, localization semantic feedback, and risk edge-case evaluation (Independent)

Don't discloseText

Labeled and evaluated fintech P2P transaction and fraud signals by monitoring and auditing high-frequency digital asset activity across international platforms. Converted unstructured localized user experience feedback into structured text data to support machine learning product-market fit. Assessed account access and security breach edge cases and documented data entry anomalies for improved risk-mitigation algorithm performance. • Tagged fraudulent behavior patterns and anomalous accounts • Structured qualitative localization feedback into labeled text • Categorized risk and edge cases for model improvement • Recorded anomalies to refine taxonomy and QA rules

Present

Geospatial Data Annotator & Surveyor (Fieldwork) — spatial semantic segmentation and ground-truth verification (Laikipia University Ecosystem)

Segmentation

Conducted spatial semantic segmentation of real-world environments by annotating and mapping land use patterns and urban land classifications. Performed ground-truth verification by collecting and auditing physical coordinates in the field against digital maps. Built accurate foundational geospatial datasets to support regional planning models using structured labeling guidance. • Annotated complex terrain and land-use categories • Verified GPS/geodetic coordinates against digital layers • Categorized transport networks and structural assets • Prepared labeled outputs for GIS-based analysis

2025

Education

Work History