Chimaroke Opara

Key Skills

Software

Appen

Labelbox

Prodigy

Lionbridge

Top Subject Matter

No subject matter listed

Top Data Types

Image

Text

Audio

Top Label Types

Bounding Box

Classification

Freelancer Overview

I am an experienced data analyst and annotation specialist with a strong background in data labeling for AI and machine learning applications. My expertise covers a wide range of annotation tasks, including text, image, audio, and video labeling, as well as bounding box and polygon annotation, named entity recognition (NER), sentiment and intent classification, and data cleaning. I am skilled in developing annotation guidelines, validating datasets, and ensuring inter-annotator agreement to maintain high data quality. I am proficient with tools and languages such as Python, SQL, Power BI, Excel, and statistical software like SPSS, MATLAB, and STATA. My experience spans various domains, including business analytics, risk modeling, and research, allowing me to deliver actionable insights and robust training data for AI projects. I am detail-oriented, efficient, and committed to quality delivery and effective communication across technical and non-technical teams.

Labeling Experience

Data Annotation Specialist (Appen)

AppenImageBounding Box

I annotated large datasets containing images, text, audio, and video for training AI and machine learning models. My work included labeling tasks such as entity recognition, sentiment classification, intent tagging, and semantic segmentation. I applied bounding boxes, polygons, and pixel-level segmentation for computer vision datasets. • Reviewed and validated peer annotations for quality control. • Achieved and maintained 98%+ annotation accuracy across projects. • Collaborated with AI engineers to clarify labeling standards. • Used tools to improve dataset reliability and consistency.

I annotated large datasets containing images, text, audio, and video for training AI and machine learning models. My work included labeling tasks such as entity recognition, sentiment classification, intent tagging, and semantic segmentation. I applied bounding boxes, polygons, and pixel-level segmentation for computer vision datasets. • Reviewed and validated peer annotations for quality control. • Achieved and maintained 98%+ annotation accuracy across projects. • Collaborated with AI engineers to clarify labeling standards. • Used tools to improve dataset reliability and consistency.

2025 - 2026

AI Training & Data Labeling Associate (Ellasot)

AppenTextClassification

I contributed to the training of NLP and speech recognition models through labeled conversational and multilingual datasets. My role involved conducting audio transcription, intent tagging, and labeling inconsistencies for feedback. I consistently exceeded daily annotation quotas while maintaining high quality. • Labeled conversational data for chatbot optimization. • Transcribed and tagged German–English audio datasets. • Identified and corrected inconsistencies in training data. • Enhanced model performance through corrective feedback.

I contributed to the training of NLP and speech recognition models through labeled conversational and multilingual datasets. My role involved conducting audio transcription, intent tagging, and labeling inconsistencies for feedback. I consistently exceeded daily annotation quotas while maintaining high quality. • Labeled conversational data for chatbot optimization. • Transcribed and tagged German–English audio datasets. • Identified and corrected inconsistencies in training data. • Enhanced model performance through corrective feedback.

2024 - 2025

Speech & Audio Data Labeling Specialist

LionbridgeAudioClassification

In Speech & Audio Data Labeling, I transcribed and annotated German and English audio recordings to support ASR system improvements. I tagged speech patterns and nuanced linguistic features for language model training. My work ensured high quality multilingual audio datasets for machine learning. • Transcribed bilingual audio recordings. • Annotated data for automatic speech recognition (ASR) models. • Labeled speech patterns and linguistic nuances. • Maintained quality and consistency in multilingual datasets.

In Speech & Audio Data Labeling, I transcribed and annotated German and English audio recordings to support ASR system improvements. I tagged speech patterns and nuanced linguistic features for language model training. My work ensured high quality multilingual audio datasets for machine learning. • Transcribed bilingual audio recordings. • Annotated data for automatic speech recognition (ASR) models. • Labeled speech patterns and linguistic nuances. • Maintained quality and consistency in multilingual datasets.

2022 - 2022

NLP Sentiment & Intent Classification Specialist

ProdigyTextClassification

For NLP Sentiment & Intent Classification, I categorized text data to train and optimize models for sentiment analysis and intent recognition. I refined ambiguous classifications to improve dataset consistency. This experience strengthened my skills in text annotation methodologies. • Classified text data for sentiment and intent models. • Improved labeling consistency through refined guidelines. • Maintained high data accuracy standards. • Supported machine learning model development with annotated data.

For NLP Sentiment & Intent Classification, I categorized text data to train and optimize models for sentiment analysis and intent recognition. I refined ambiguous classifications to improve dataset consistency. This experience strengthened my skills in text annotation methodologies. • Classified text data for sentiment and intent models. • Improved labeling consistency through refined guidelines. • Maintained high data accuracy standards. • Supported machine learning model development with annotated data.

2022 - 2022

Computer Vision Annotation Project Participant

LabelboxImageBounding Box

In the Computer Vision Annotation Project, I labeled thousands of images using bounding boxes and object detection tools. I performed quality checks on labeled datasets to ensure high consistency and accuracy. My work supported the enhancement of computer vision AI models. • Used object detection and annotation tools for labeling. • Conducted routine data quality reviews. • Maintained strict dataset accuracy standards. • Improved overall model effectiveness through precise annotations.

In the Computer Vision Annotation Project, I labeled thousands of images using bounding boxes and object detection tools. I performed quality checks on labeled datasets to ensure high consistency and accuracy. My work supported the enhancement of computer vision AI models. • Used object detection and annotation tools for labeling. • Conducted routine data quality reviews. • Maintained strict dataset accuracy standards. • Improved overall model effectiveness through precise annotations.

2022 - 2022

Education

Work History