Hassan Motist

Key Skills

Software

Appen

Top Subject Matter

CV Analysis

Talent Screening

Job Matching

Top Data Types

Text

Audio

Document

Top Task Types

Text Generation

Data Collection

Classification

Freelancer Overview

I am a Master’s student in Intelligent Systems Engineering with a technical background in MERN development, offering a unique blend of data annotation experience and engineering expertise. My professional background includes working as a Linguistic Data Collector at Appen, where I managed audio and text datasets, and a role at Grande Charte focused on automating product data collection and labeling workflows. These experiences have provided me with a deep understanding of data consistency, structured collection, and the rigorous classification rules required for high-quality AI training. What sets me apart is my ability to bridge the gap between manual labeling and complex AI architecture. I have successfully designed and deployed a RAG architecture for semantic CV analysis using ChromaDB and LLM APIs, giving me firsthand insight into how data quality directly influences model retrieval and accuracy . Combined with a C1 Advanced English certification, I am equipped to handle sophisticated technical annotation, documentation, and metadata validation within agile environments.

Labeling Experience

Full Stack Developer & AI

Computer Code ProgrammingComputer Programming Coding

Automated product data collection and structuring using MERN stack. Labeled and categorized datasets to optimize recommendation accuracy. Validated data consistency and metadata quality in Agile sprints. Developed technical annotation guidelines and workflows in English.

Automated product data collection and structuring using MERN stack. Labeled and categorized datasets to optimize recommendation accuracy. Validated data consistency and metadata quality in Agile sprints. Developed technical annotation guidelines and workflows in English.

2025 - 2025

Dataset Labeler (Product Categorization)

DocumentClassification

I labeled and categorized datasets to enhance product recommendation systems in an e-commerce context. Automation and workflow improvements using MERN tools were applied to optimize labeling accuracy. Data validation and guideline development ensured consistent annotation in team settings. • Applied categorization techniques to product datasets • Automated and structured product data with full stack technologies • Authored English annotation instruction sets for accurate task execution • Validated dataset integrity and metadata consistency during Agile sprints

I labeled and categorized datasets to enhance product recommendation systems in an e-commerce context. Automation and workflow improvements using MERN tools were applied to optimize labeling accuracy. Data validation and guideline development ensured consistent annotation in team settings. • Applied categorization techniques to product datasets • Automated and structured product data with full stack technologies • Authored English annotation instruction sets for accurate task execution • Validated dataset integrity and metadata consistency during Agile sprints

2025 - 2025

Data Collector

AppenAudioData Collection

I collected and structured over 40 hours of audio and text datasets for use in AI training workflows. The work focused on preparing high-quality audio and text data for machine learning systems. Each dataset underwent basic consistency checks and formatting prior to submission. • Managed large volumes of raw audio and text for annotation preparation • Ensured all data adhered to project-specific consistency criteria • Organized datasets into formats conducive for ML pipeline integration • Supported downstream annotation and labeling processes

I collected and structured over 40 hours of audio and text datasets for use in AI training workflows. The work focused on preparing high-quality audio and text data for machine learning systems. Each dataset underwent basic consistency checks and formatting prior to submission. • Managed large volumes of raw audio and text for annotation preparation • Ensured all data adhered to project-specific consistency criteria • Organized datasets into formats conducive for ML pipeline integration • Supported downstream annotation and labeling processes

2025 - 2025

Education

Work History