Key Skills

Software

Labelbox

SuperAnnotate

CVAT

Top Subject Matter

General machine learning datasets

Text data for NLP applications

E-commerce product data

Top Data Types

Image

Text

Audio

Document

Top Task Types

Bounding Box

Entity (NER) Classification

Classification

Emotion Recognition

Transcription

Freelancer Overview

Data Annotator (Freelance / Remote). Core strengths include Labelbox, SuperAnnotate, and CVAT. Education includes Bachelor of Science, University of Florida (2024). AI-training focus includes data types such as Image, Text, and Audio and labeling workflows including Bounding Box, Entity (NER) Classification, and Classification.

Labeling Experience

Data Annotator (Freelance / Remote)

LabelboxImageBounding Box

As a Data Annotator, I labeled objects and validated image datasets for machine learning model training. I consistently maintained a high standard of accuracy and improved annotation guideline consistency. Quality assurance reviews confirmed over 98% accuracy for my labeling efforts. • Labeled objects in images using bounding boxes and segmentation • Performed sentiment analysis and named entity recognition on text data • Annotated over 500,000 data points across diverse datasets • Utilized annotation tools Labelbox, CVAT, and SuperAnnotate for project tasks

As a Data Annotator, I labeled objects and validated image datasets for machine learning model training. I consistently maintained a high standard of accuracy and improved annotation guideline consistency. Quality assurance reviews confirmed over 98% accuracy for my labeling efforts. • Labeled objects in images using bounding boxes and segmentation • Performed sentiment analysis and named entity recognition on text data • Annotated over 500,000 data points across diverse datasets • Utilized annotation tools Labelbox, CVAT, and SuperAnnotate for project tasks

2024 - Present

Data Labeling Specialist (Contract Role)

LabelboxTextEntity Ner Classification

As a Data Labeling Specialist, I reviewed and corrected annotated text datasets to improve machine learning accuracy. I collaborated closely with QA teams to refine and enhance data annotation workflows. My work focused on identifying and reducing recurring labeling errors in delivered datasets. • Reviewed and corrected annotated datasets in CSV and JSON formats • Collaborated with quality assurance teams to enhance workflows • Applied named entity recognition for chatbot and information extraction tasks • Used industry tools such as Labelbox and CVAT for annotation refinement

As a Data Labeling Specialist, I reviewed and corrected annotated text datasets to improve machine learning accuracy. I collaborated closely with QA teams to refine and enhance data annotation workflows. My work focused on identifying and reducing recurring labeling errors in delivered datasets. • Reviewed and corrected annotated datasets in CSV and JSON formats • Collaborated with quality assurance teams to enhance workflows • Applied named entity recognition for chatbot and information extraction tasks • Used industry tools such as Labelbox and CVAT for annotation refinement

2024 - 2024

Audio Annotator—Audio Annotation & Transcription (Project)

CVATAudioTranscription

For an audio annotation and transcription project, I transcribed, labeled, and tagged features in audio datasets for speech and speaker analysis. Tasks included tagging speakers, accents, and background noise for training speech models. My careful annotations contributed to high-quality labeled audio data for AI development. • Transcribed and labeled audio datasets for speaker identification • Tagged accents, speaker roles, and background noises • Ensured audio data quality and fidelity for speech model development • Maintained high accuracy standards throughout transcription tasks

For an audio annotation and transcription project, I transcribed, labeled, and tagged features in audio datasets for speech and speaker analysis. Tasks included tagging speakers, accents, and background noise for training speech models. My careful annotations contributed to high-quality labeled audio data for AI development. • Transcribed and labeled audio datasets for speaker identification • Tagged accents, speaker roles, and background noises • Ensured audio data quality and fidelity for speech model development • Maintained high accuracy standards throughout transcription tasks

2023 - 2023

Data Annotator—Named Entity Recognition (Project)

LabelboxTextEntity Ner Classification

As part of a named entity recognition (NER) initiative, I annotated names, dates, and locations within diverse text corpora to train chatbot and information extraction systems. I focused on improving annotation speed and accuracy in a production environment. My contributions improved the model's entity detection for end-user applications. • Labeled entities such as names, dates, and locations • Improved chatbot understanding with accurate entity labeling • Enhanced downstream performance in information extraction • Refined annotation guidelines for NER consistency

As part of a named entity recognition (NER) initiative, I annotated names, dates, and locations within diverse text corpora to train chatbot and information extraction systems. I focused on improving annotation speed and accuracy in a production environment. My contributions improved the model's entity detection for end-user applications. • Labeled entities such as names, dates, and locations • Improved chatbot understanding with accurate entity labeling • Enhanced downstream performance in information extraction • Refined annotation guidelines for NER consistency

2023 - 2023

Data Annotator—Social Media Sentiment Analysis (Project)

CVATTextEmotion Recognition

On a social media sentiment analysis project, I labeled posts as positive, negative, or neutral to inform analytics and moderation systems. I managed the special challenges of handling slang, sarcasm, and nuanced context. My work enhanced sentiment models for better understanding of online conversations. • Labeled thousands of social media posts for sentiment analysis • Adapted to dynamic slang and colloquial language trends • Supported improved content moderation via accurate sentiment labeling • Enhanced analytics for brand and user engagement analysis

On a social media sentiment analysis project, I labeled posts as positive, negative, or neutral to inform analytics and moderation systems. I managed the special challenges of handling slang, sarcasm, and nuanced context. My work enhanced sentiment models for better understanding of online conversations. • Labeled thousands of social media posts for sentiment analysis • Adapted to dynamic slang and colloquial language trends • Supported improved content moderation via accurate sentiment labeling • Enhanced analytics for brand and user engagement analysis

2023 - 2023

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Education

Work History