Samuel W.

Key Skills

Software

Supervisely

Top Subject Matter

Computer vision and text classification datasets

Records management and digital data organization

Top Data Types

Image

Text

Top Task Types

Bounding Box

Classification

Entity (NER) Classification

Freelancer Overview

Data Annotation Practice (Coursework & Self-directed) — Supervisely. Brings 1+ years of professional experience across complex professional workflows, research, and quality-focused execution. Core strengths include Supervisely. Education includes Bachelor of Science, Dedan Kimathi University of Technology (2025). AI-training focus includes data types such as Image and Text and labeling workflows including Bounding Box, Classification, and Named Entity Recognition.

Labeling Experience

IT Attachment / Intern — TWWDA

ImageBounding BoxClassification

Supported organizational data entry, records management, and digital file organization as part of an IT attachment role. While the work was not explicitly framed as AI/data annotation, it involved maintaining accurate structured records that align with data curation practices. Ensured consistency and correctness of entries and maintained organized digital information for operational use. • Performed data entry and records management • Maintained accurate and consistent digital file organization • Organized and curated records for internal access • Provided general technical support alongside data handling tasks

2025 - 2025

Data Annotation Practice (Coursework & Self-directed) — Supervisely

SuperviselyImageBounding BoxClassification

Performed supervised data labeling in Supervisely across image and text datasets following provided annotation guidelines. Applied consistent annotation formats for image tasks (object/bounding box) and for text classification/categorization. Reviewed outputs by correcting and re-labeling data to improve accuracy and consistency. • Labeled images with object/bounding box annotations in Supervisely • Labeled text using classification and categorization labels • Validated and corrected annotated samples for consistency • Repeated practice to improve adherence to labeling rules

2024 - 2025

Education

Work History