Nada Hanad

Key Skills

Software

AWS SageMaker

Dataloop

LabelImg

Label Studio

Redbrick AI

SuperAnnotate

Internal/Proprietary Tooling

Top Subject Matter

Text Classification

Data Annotation

LLM Hallucination

Top Data Types

Audio

Document

Text

Top Task Types

Audio Recording

Classification

Fine Tuning

Text Generation

Text Summarization

Freelancer Overview

As a Fullstack Developer with experience in data labeling and AI training, I have worked on projects involving text and media analysis using a combination of full-stack technologies like ReactJS, NestJS, and machine learning models. I have developed tools to simulate and analyze advertising behavior, applying text classification to detect false ads. My hands-on experience with labeling techniques, particularly for natural language processing, sets me apart in building accurate datasets for AI model training. My background in agile team environments has further honed my ability to deliver high-quality, scalable solutions.

Reviews (1)

Labeling Experience

French Web Developer – AI Data Labeling (HTML/CSS/JS)

Internal Proprietary ToolingComputer Code ProgrammingQuestion AnsweringComputer Programming Coding

Contributed to an AI training project focused on improving web understanding through annotated code. Tasks included analyzing French HTML/CSS/JS webpage screenshots, generating code edits, writing question–answer pairs, identifying bugs, and improving UI/UX behavior. The project required attention to detail, strong frontend development skills, and fluency in French. Quality and consistency were monitored through peer reviews and detailed guidelines.

Contributed to an AI training project focused on improving web understanding through annotated code. Tasks included analyzing French HTML/CSS/JS webpage screenshots, generating code edits, writing question–answer pairs, identifying bugs, and improving UI/UX behavior. The project required attention to detail, strong frontend development skills, and fluency in French. Quality and consistency were monitored through peer reviews and detailed guidelines.

2024 - 2024

Arabic Audio Transcription and Dialect Annotation Project

Label StudioAudioText Generation

Worked on Arabic dialect transcription data, focusing on noisy, war-related recordings across Maghrebi, Levantine, Egyptian, and Iraqi dialects. Designed linguistic rules and a unified normalization dictionary to standardize variations in number spellings, phonetic inconsistencies, and dialectal expressions. Emphasized phonetic accuracy, dialectal realism, and data consistency to support large-scale ASR training and evaluation. Key Contributions: - Created a comprehensive number normalization dictionary for digits 11–19 across dialects. - Defined transcription guidelines for orthographic consistency (e.g., hamza placement, “ة” vs “ه”, “يّ” with shadda). - Developed dialect-aware normalization rules for swear words, filler phrases, and jargon. - Ensured quality control in annotated corpora with a focus on phonetic integrity and training fairness.

Worked on Arabic dialect transcription data, focusing on noisy, war-related recordings across Maghrebi, Levantine, Egyptian, and Iraqi dialects. Designed linguistic rules and a unified normalization dictionary to standardize variations in number spellings, phonetic inconsistencies, and dialectal expressions. Emphasized phonetic accuracy, dialectal realism, and data consistency to support large-scale ASR training and evaluation. Key Contributions: - Created a comprehensive number normalization dictionary for digits 11–19 across dialects. - Defined transcription guidelines for orthographic consistency (e.g., hamza placement, “ة” vs “ه”, “يّ” with shadda). - Developed dialect-aware normalization rules for swear words, filler phrases, and jargon. - Ensured quality control in annotated corpora with a focus on phonetic integrity and training fairness.

2024 - 2024

Generative AI Risk Analysis in Advertising

Aws SagemakerTextClassificationText Generation

Conducted a risk analysis for generative AI in advertising by evaluating Large Language Models (LLMs) in real-world environments. Labeled and analyzed text data generated by LLMs to assess the presence of hallucinations and the overall effectiveness of AI-generated ads. The project focused on evaluating ad variations and their impact on target audiences, ensuring the accuracy and relevance of AI-generated content. Worked closely with teams to improve system performance and applied classification models to enhance ad integrity and trustworthiness.

Conducted a risk analysis for generative AI in advertising by evaluating Large Language Models (LLMs) in real-world environments. Labeled and analyzed text data generated by LLMs to assess the presence of hallucinations and the overall effectiveness of AI-generated ads. The project focused on evaluating ad variations and their impact on target audiences, ensuring the accuracy and relevance of AI-generated content. Worked closely with teams to improve system performance and applied classification models to enhance ad integrity and trustworthiness.

2023 - 2024

Education

Work History