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Hannah Stern

Hannah Stern

AI Trainer: Crafting the Future, One Model at a Time

USA flagNew York, Usa
$10.00/hrIntermediateAppenClickworkerCrowdsource

Key Skills

Software

AppenAppen
ClickworkerClickworker
CrowdSourceCrowdSource
CVATCVAT
Data Annotation TechData Annotation Tech
LabelboxLabelbox
LabelImgLabelImg
OneFormaOneForma
RemotasksRemotasks
SuperAnnotateSuperAnnotate
TolokaToloka
Scale AIScale AI

Top Subject Matter

No subject matter listed

Top Data Types

AudioAudio
ImageImage
TextText

Top Task Types

Bounding Box
Classification
Evaluation Rating
Object Detection
Segmentation

Freelancer Overview

I am a professional with expertise in AI training and data labeling, possessing hands-on experience in annotating text, images, audio, video, and geospatial data. I am proficient in various labeling techniques, including classification, bounding boxes, segmentation, named entity recognition (NER), and evaluation/rating. My efforts are focused on ensuring high levels of accuracy, consistency, and quality, which are critical for the development of reliable artificial intelligence systems. With a solid foundation in data science, mathematics, and research, I demonstrate strong analytical abilities and meticulous attention to detail. I am well-versed in a range of annotation tools, including Makesense.ai, LabelImg, and CVAT. I have effectively managed high-volume datasets and conducted quality assurance checks to deliver training data that enhances AI performance across multiple sectors, including technology, healthcare, and e-commerce.

IntermediateSwahiliEnglishSpanish

Labeling Experience

CVAT

Data Annotation

CVATImageBounding Box
Bounding boxes were used in CVAT to annotate large image datasets for object detection tasks. Road signs, cars, pedestrians, and commonplace items were accurately labeled to aid in computer vision training. Achieved consistent accuracy above 95% by adhering to project guidelines and conducting cross-check reviews to ensure quality.

Bounding boxes were used in CVAT to annotate large image datasets for object detection tasks. Road signs, cars, pedestrians, and commonplace items were accurately labeled to aid in computer vision training. Achieved consistent accuracy above 95% by adhering to project guidelines and conducting cross-check reviews to ensure quality.

2025 - 2025

Education

R

Rice University

Doctor of Philosophy, Mathematics & Statistics

Doctor of Philosophy
2024 - 2024
R

Rice University

Master of Science, Mathematics & IT (Data Science & Machine Learning)

Master of Science
2021 - 2021

Work History

S

Southern Methodist University

Senior Researcher & QA Specialist

Dallas
2023 - Present
R

Rice University

Mathematics Consultant & Data Analyst

Houston
2021 - 2022