Quentine N.

Key Skills

Software

Other

CVAT

Top Subject Matter

AI/ML training datasets (text annotation and categorization)

Digital datasets (text categorization and tagging)

AI/ML model improvement (image annotation and validation)

Top Data Types

Text

Image

Top Task Types

Entity (NER) Classification

Classification

Freelancer Overview

Freelance Data Annotator (2021–2026). Brings 7+ years of professional experience across complex professional workflows, research, and quality-focused execution. Core strengths include Other and CVAT. Education includes Bachelor of Arts, N/A. AI-training focus includes data types such as Text and Image and labeling workflows including Entity (NER) Classification and Classification.

Labeling Experience

Remote AI Data Contributor (2021–2026)

CVATImageClassification

Contributed to remote AI model improvement through accurate data annotation and data validation. Labeled image and associated dataset content to help strengthen model performance. Carried out quality assurance steps to ensure annotations were reliable for training and evaluation.• Annotated image data for AI training pipelines• Validated and reviewed annotations for quality and consistency• Assisted in refining datasets used for model improvement• Ensured that labeled outputs met accuracy expectations

2021 - 2026

Freelance Data Annotator (2021–2026)

OtherTextEntity (NER) Classification

Annotated and labeled text data for AI and machine learning training. Performed categorization and tagging to support dataset accuracy and downstream model behavior. Conducted data validation checks to ensure label consistency and quality.• Labeled and verified text samples for classification datasets• Applied consistent tagging guidelines across examples• Supported AI model training by preparing clean labeled outputs• Reviewed labeling quality and corrected inconsistencies as needed

2021 - 2026

Data Labeling Specialist (2020–2026)

OtherTextClassification

Performed data labeling for digital datasets including categorization and quality checks. Focused on maintaining accuracy standards and ensuring task consistency. Supported dataset readiness through verification and quality control workflows.• Applied labels for text-based digital dataset categories• Conducted quality checks and verification of labeled data• Ensured labeling guideline adherence across batches• Prepared datasets for AI training by validating label integrity

2020 - 2026

Education

Work History