Agnes

Key Skills

Software

iMerit

Remotasks

Sama

Top Subject Matter

No subject matter listed

Top Data Types

Audio

Computer Code Programming

Document

Image

Top Label Types

Audio Recording

Classification

Computer Programming Coding

Data Collection

Entity Ner Classification

Evaluation Rating

Question Answering

Transcription

Freelancer Overview

I am a Data Analyst and AI Training Specialist with 3 years of experience in data annotation, validation, and quality review for AI systems. My background includes hands-on work training and evaluating models using structured datasets, following detailed annotation guidelines, and reviewing outputs for accuracy, bias, bias mitigation, and consistency. I am proficient in Python, R, SQL, SPSS, and Excel, and have supported projects involving text and audio annotation, transcription review, and data cleaning. With a strong foundation in applied statistics and extensive experience in academic and professional research writing, I deliver high-quality, reliable data that supports robust and ethical AI development. I thrive in fully remote, cross-cultural teams and am known for clear communication, attention to detail, and consistent delivery.

Labeling Experience

Text & Audio Data Annotation for AI Model Training

SamaAudioEntity Ner ClassificationEvaluation Rating

Worked on large-scale AI training projects focused on text and audio data annotation for natural language processing systems. Tasks included labeling and classifying text for intent, sentiment, and entity recognition (NER), reviewing and correcting AI-generated transcriptions, and rating model outputs for accuracy, relevance, and bias. The project involved thousands of data samples across multiple batches, following strict annotation guidelines and quality standards. I consistently met productivity and quality benchmarks while maintaining high accuracy and consistency across tasks. Regular audits and peer reviews were used to ensure reliable outputs.

Worked on large-scale AI training projects focused on text and audio data annotation for natural language processing systems. Tasks included labeling and classifying text for intent, sentiment, and entity recognition (NER), reviewing and correcting AI-generated transcriptions, and rating model outputs for accuracy, relevance, and bias. The project involved thousands of data samples across multiple batches, following strict annotation guidelines and quality standards. I consistently met productivity and quality benchmarks while maintaining high accuracy and consistency across tasks. Regular audits and peer reviews were used to ensure reliable outputs.

2022 - 2024

Education

Work History