Shoaib Hassan

Key Skills

Software

AWS SageMaker

Appen

Clickworker

CVAT

Labelbox

Prodigy

SuperAnnotate

Top Subject Matter

No subject matter listed

Top Data Types

Image

Text

Video

Top Task Types

Bounding Box

Computer Programming Coding

Evaluation Rating

Point Key Point

Polygon

Freelancer Overview

Labelled and validated large volumes of image, audio, and text data for various AI/ML clients via platforms like Upwork, Scale AI, and private contractors. Performed bounding box, polygon, keypoint, and segmentation annotations for object detection models in retail and autonomous vehicle datasets. Annotated chat and transcript data for training NLP models in intent recognition and contextual analysis. Delivered over 95%+ accuracy consistently, earning top-tier reviewer ratings from clients. Assisted in training new annotators and reviewing peer labels for quality assurance. Collaborated with a machine learning team to annotate healthcare-related image datasets (X-rays, MRIs) using supervised tools. Labelled thousands of medical terms and entities for clinical NLP tasks. Participated in weekly guideline update meetings to improve label consistency and project outcomes. Identified edge cases and provided feedback that improved annotation manuals and reduced error rates by 20%. Collaborated with a machine learning team to annotate healthcare-related image datasets (X-rays, MRIs) using supervised tools. Labelled thousands of medical terms and entities for clinical NLP tasks. Participated in weekly guideline update meetings to improve label consistency and project outcomes. Identified edge cases and provided feedback that improved annotation manuals and reduced error rates by 20%. Self-Directed Annotation Portfolio: Created a mini project involving bounding box annotations.

Labeling Experience

Data Annotation Intern - AI project

CVATImageBounding BoxPolygon

Collaborated with a machine learning team to annotate healthcare-related image datasets (X-rays, MRIs) using supervised tools. Labeled thousands of medical terms and entities for clinical NLP tasks. Participated in weekly guideline update meetings to improve label consistency and project outcomes. Identified edge cases and provided feedback that improved annotation manuals and reduced error rates by 20%.

Collaborated with a machine learning team to annotate healthcare-related image datasets (X-rays, MRIs) using supervised tools. Labeled thousands of medical terms and entities for clinical NLP tasks. Participated in weekly guideline update meetings to improve label consistency and project outcomes. Identified edge cases and provided feedback that improved annotation manuals and reduced error rates by 20%.

2021 - 2024

Education

Work History