Noaman Noaman

Key Skills

Software

CVAT

Prodigy

Appen

Top Subject Matter

Computer Vision (Autonomous Driving, Medical Imaging, Retail Analytics)

Natural Language Processing (E-commerce, Social Media, Chatbots)

Image Classification

Top Data Types

Image

Text

Top Task Types

Bounding Box

Entity Ner Classification

Classification

Freelancer Overview

Senior Data Annotation Specialist. Core strengths include CVAT, Prodigy, and Appen. Education includes Bachelor of Science, University of Karachi (2020). AI-training focus includes data types such as Image and Text and labeling workflows including Bounding Box, Entity (NER) Classification, and Classification.

Labeling Experience

Senior Data Annotation Specialist

CVATImageBounding Box

As a Senior Data Annotation Specialist at RemoteTask AI Solutions, I labeled images for computer vision projects targeting autonomous vehicles, medical imaging, and retail analytics. I used bounding box, polygon, and semantic segmentation methods to annotate over 2,000 images per week. My role required a high degree of accuracy, with ongoing quality assurance and iterative improvements based on ML engineer feedback. • Annotated over 200,000 images since start of tenure. • Maintained a consistent 98.5% accuracy rate. • Utilized CVAT, Labelbox, and SuperAnnotate platforms daily. • Mentored and trained 5 junior team members on annotation best practices.

As a Senior Data Annotation Specialist at RemoteTask AI Solutions, I labeled images for computer vision projects targeting autonomous vehicles, medical imaging, and retail analytics. I used bounding box, polygon, and semantic segmentation methods to annotate over 2,000 images per week. My role required a high degree of accuracy, with ongoing quality assurance and iterative improvements based on ML engineer feedback. • Annotated over 200,000 images since start of tenure. • Maintained a consistent 98.5% accuracy rate. • Utilized CVAT, Labelbox, and SuperAnnotate platforms daily. • Mentored and trained 5 junior team members on annotation best practices.

2022 - Present

NLP Data Annotator

ProdigyTextEntity Ner Classification

As an NLP Data Annotator at DataPrime Technologies, I performed text annotation for projects in e-commerce and social media. Tasks included named entity recognition, part-of-speech tagging, and intent classification for multilingual datasets. I executed data validation checks and maintained high standards of annotation consistency and accuracy. • Labeled more than 15,000 text samples for sentiment analysis. • Supported chatbot training with English, Urdu, and Arabic datasets. • Utilized Prodigy and Label Studio extensively for labeling workflows. • Cross-checked annotations to ensure project quality requirements were met.

As an NLP Data Annotator at DataPrime Technologies, I performed text annotation for projects in e-commerce and social media. Tasks included named entity recognition, part-of-speech tagging, and intent classification for multilingual datasets. I executed data validation checks and maintained high standards of annotation consistency and accuracy. • Labeled more than 15,000 text samples for sentiment analysis. • Supported chatbot training with English, Urdu, and Arabic datasets. • Utilized Prodigy and Label Studio extensively for labeling workflows. • Cross-checked annotations to ensure project quality requirements were met.

2021 - 2022

Image Classification & Transcription Specialist

AppenImageClassification

As an Image Classification & Transcription Specialist for Appen, I categorized images for content moderation and search engine optimization. I also annotated facial landmarks and performed keypoint detection for facial recognition system projects. Quality ratings and search result evaluation were integral to the accuracy of datasets provided to clients. • Transcribed audio files for speech-to-text and voice recognition models. • Maintained 95%+ quality scores consistently across projects. • Classified images using set taxonomies for relevant AI model inputs. • Annotated search query results for relevance and accuracy assessment.

As an Image Classification & Transcription Specialist for Appen, I categorized images for content moderation and search engine optimization. I also annotated facial landmarks and performed keypoint detection for facial recognition system projects. Quality ratings and search result evaluation were integral to the accuracy of datasets provided to clients. • Transcribed audio files for speech-to-text and voice recognition models. • Maintained 95%+ quality scores consistently across projects. • Classified images using set taxonomies for relevant AI model inputs. • Annotated search query results for relevance and accuracy assessment.

2020 - 2021

Education

Work History