Siphokazi N.

Key Skills

Software

Appen

CVAT

Doccano

HiveMind

Labelbox

Mercor

Micro1

Clickworker

Remotasks

Scale AI

Toloka

Telus

Top Subject Matter

No subject matter listed

Top Data Types

Image

Text

Audio

Top Task Types

Bounding Box

Transcription

Data Collection

Classification

Evaluation/Rating

Freelancer Overview

I have experience working with data annotation, labeling, and AI training data projects that support the development and improvement of machine learning models. My work has involved accurately labeling text, images, audio, and structured datasets according to detailed guidelines while maintaining high quality standards and consistency. I am comfortable performing tasks such as content categorization, sentiment analysis, entity recognition, transcription review, data validation, and quality assurance. I have developed strong attention to detail, analytical thinking, and the ability to quickly learn project-specific requirements and annotation frameworks. In addition to technical labeling skills, I am proficient in using digital tools, following complex instructions, meeting productivity targets, and collaborating with distributed teams. My background has strengthened my ability to identify edge cases, maintain data integrity, and deliver reliable results that contribute to the performance of AI systems. I am committed to producing accurate, unbiased, and high-quality training data that helps build more effective and trustworthy artificial intelligence solutions.

Labeling Experience

AI Training, Data Annotation and Quality Review

TextClassification

Worked on AI training data annotation projects involving the classification, categorization, and validation of large volumes of text data used to train machine learning and natural language processing models. Responsibilities included sentiment analysis, intent classification, content moderation labeling, entity identification, and data quality review according to detailed annotation guidelines. Maintained high accuracy standards while reviewing datasets for consistency, completeness, and compliance with project requirements. Contributed to improving model performance by identifying ambiguous cases, applying labeling guidelines consistently, and providing feedback on annotation processes. Regularly performed quality assurance checks, corrected labeling discrepancies, and ensured data integrity across thousands of records. Demonstrated strong attention to detail, analytical skills, and the ability to meet productivity and quality targets in a fast-paced environment.

2024 - Present

Education