David Y.

Key Skills

Software

Clickworker

CrowdSource

CVAT

Data Annotation Tech

Dataloop

Labelbox

Sama

Other

Top Subject Matter

AI Model Training

Geospatial/Educational Data

Top Data Types

Computer Code Programming

Image

Text

Video

Top Task Types

Bounding Box

Cuboid

Data Collection

Polygon

Question Answering

Classification

Freelancer Overview

Associate, Data Annotation. Brings 3+ years of professional experience across complex professional workflows, research, and quality-focused execution. Core strengths include Sama and Other. Education includes Diploma in Information Communication Technology, Godoma Technical Training Institute (2024) and Certificate in Information Communication Technology, Godoma Technical Training Institute (2021). AI-training focus includes data types such as Image, Geospatial, and Tiled Imagery and labeling workflows including Classification and Data Collection.

Labeling Experience

Associate, Data Annotation

SamaImageClassification

I analyzed short video clips and images and provided structured annotations to enhance AI model accuracy. My work involved supporting large-scale AI model training initiatives and ensuring accurate and reliable labeling aligned with quality control standards. I maintained annotation precision at 99% while handling multiple monthly annotation projects. • Annotated video/image datasets for AI model development • Maintained 99% accuracy in assigned data annotation tasks • Supported multilingual AI dataset projects • Utilized controlled quality measures to verify high volumes of entries.

2025 - 2026

GPS Field Data Collector

OtherData Collection

I collected and validated GPS-based geospatial data to ensure dataset integrity for mapping and analysis purposes. My efforts reduced errors by 20% and enhanced the accessibility and structure of digital records. I communicated validated findings to key stakeholders involved in education. • Gathered GPS geospatial imagery and location data • Performed dataset validation and data integrity checks • Organized and maintained digital geospatial records • Supported data-driven educational policy through accurate collection.

2024 - 2024

DBE LIDAR

Labelbox3D SensorBounding BoxPolygon

Identifying and classifying objects within the point cloud data, such as roads, lanes, vehicles, pedestrians, and obstacles. Annotated LiDAR data serves as the foundation for training machine learning models that enable the self-driving system to interpret and understand its environment.

2022 - 2024

Education

Work History