Zoom D.

Key Skills

Software

No software listed

Top Subject Matter

Image object annotation

Sentiment analysis and keyword tagging

AI response evaluation

Top Data Types

Image

Text

Document

Top Task Types

Bounding Box

Classification

Freelancer Overview

Image Annotation Practice (Data Annotator / AI Data Labeler). Core strengths include N, A, and Google Sheets. Education includes High School Diploma, Commonwealth High School (2023). AI-training focus includes data types such as Image and Text and labeling workflows including Bounding Box, Classification, and Evaluation.

Labeling Experience

AI Response Evaluation Practice (AI Data Labeler)

Text

Reviewed AI-generated responses to assess relevance and clarity for basic AI response evaluation tasks. Identified incorrect, low-quality, or problematic outputs based on task criteria to support dataset improvement. Ensured evaluations followed provided instructions and rating expectations during the practice period.• Checked AI responses for relevance to the prompt/context.• Assessed clarity and usefulness of the generated text.• Flagged incorrect or low-quality responses for correction or exclusion.• Performed consistent evaluations aligned with the guidelines.

2025 - Present

Text Annotation Practice (Data Annotator / AI Data Labeler)

TextClassification

Performed text annotation by categorizing sentiment labels and tagging keywords for structured datasets. Evaluated and applied annotation guidelines to produce accurate, consistent sentiment and keyword outputs. Focused on producing high-quality labels suitable for downstream AI or analytics tasks.• Assigned sentiment categories (positive, neutral, negative) to text inputs.• Tagged relevant keywords to support structured dataset creation.• Maintained consistency in label assignment across multiple examples.• Followed instructions and quality checks to ensure label accuracy.

2025 - Present

Image Annotation Practice (Data Annotator / AI Data Labeler)

ImageBounding Box

Labeled image data by drawing bounding boxes around target objects, prioritizing annotation accuracy and consistency across samples. Followed detailed task instructions and applied guidelines to maintain label quality throughout the practice period. Performed ongoing checks for correctness and uniformity when handling multiple images.• Created bounding box annotations for labeled objects with attention to object boundaries.• Ensured consistent labeling across a set of repeated or related samples.• Validated outputs against guideline expectations for accuracy and completeness.• Completed tasks reliably within the practice workflow.

2025 - Present

Education

Work History