Waeni Nzioka

Key Skills

Software

Labelbox

Top Subject Matter

AI and Machine Learning Training Data

Top Data Types

Text

Image

Top Task Types

Classification

Freelancer Overview

Data Labelling & Annotation Specialist. Core strengths include Labelbox. Education includes Bachelor of Science, University of Nairobi. AI-training focus includes data types such as Text and labeling workflows including Classification, Evaluation, and Rating.

Labeling Experience

Data Quality Reviewer

LabelboxText

As a Data Quality Reviewer, I was responsible for auditing labeled datasets to ensure consistency and identify annotation errors. I provided feedback to annotators to enhance accuracy and reduce rework while supporting project managers in tracking progress. I contributed to the development and refinement of annotation guidelines and training materials. • Reviewed labeled text and image datasets for quality assurance • Gave direct feedback to annotation specialists • Audited guideline compliance and flagged deviations • Collaborated on project delivery timelines and process improvement

As a Data Quality Reviewer, I was responsible for auditing labeled datasets to ensure consistency and identify annotation errors. I provided feedback to annotators to enhance accuracy and reduce rework while supporting project managers in tracking progress. I contributed to the development and refinement of annotation guidelines and training materials. • Reviewed labeled text and image datasets for quality assurance • Gave direct feedback to annotation specialists • Audited guideline compliance and flagged deviations • Collaborated on project delivery timelines and process improvement

Present

Data Labelling & Annotation Specialist

LabelboxTextClassification

As a Data Labelling & Annotation Specialist, I managed a high volume of annotation tasks across text, image, and audio data types for regulated AI and machine learning pipelines. I followed detailed annotation guidelines for sentiment, intent, named entities, and bounding boxes, maintaining high inter-annotator agreement. I regularly identified edge cases to refine annotation schemas and met throughput targets while ensuring high accuracy. • Executed text sentiment and intent classification and named entity recognition • Labeled images with bounding boxes and conducted audio transcription tasks • Used annotation platforms including Scale AI, Appen, Labelbox, Amazon MTurk, and CVAT • Contributed feedback on ambiguous cases to improve annotation processes

As a Data Labelling & Annotation Specialist, I managed a high volume of annotation tasks across text, image, and audio data types for regulated AI and machine learning pipelines. I followed detailed annotation guidelines for sentiment, intent, named entities, and bounding boxes, maintaining high inter-annotator agreement. I regularly identified edge cases to refine annotation schemas and met throughput targets while ensuring high accuracy. • Executed text sentiment and intent classification and named entity recognition • Labeled images with bounding boxes and conducted audio transcription tasks • Used annotation platforms including Scale AI, Appen, Labelbox, Amazon MTurk, and CVAT • Contributed feedback on ambiguous cases to improve annotation processes

Present

Education

Work History