Jinadu A.

Key Skills

Software

Scale AI

Top Subject Matter

Finance

Resarch and analysis

Data Analysis

Top Data Types

Image

Text

Top Task Types

Transcription

Bounding Box

Text Generation

Freelancer Overview

I have experience contributing to AI training and data evaluation projects through Outlier, where I reviewed and assessed AI-generated responses for accuracy, relevance, clarity, and overall quality. My work involved following detailed project guidelines, conducting research and fact-checking, identifying errors, and providing constructive feedback to improve model performance. This experience strengthened my attention to detail, analytical thinking, and ability to maintain high-quality standards while working independently in a remote environment. As a Finance undergraduate at Federal University Oye-Ekiti, I have developed strong quantitative, research, and problem-solving skills that complement AI training and data annotation work. I am proficient in data analysis, internet research, content evaluation, Microsoft Excel, and quality assurance processes. My combination of academic training, AI evaluation experience, and commitment to accuracy enables me to contribute effectively to data labeling, AI model training, and content review projects.

Labeling Experience

AI Contributor

ImageText Generation

Project Scope:Contributed to AI training and evaluation projects designed to improve the accuracy, safety, relevance, and overall quality of large language model outputs. The project focused on reviewing AI-generated content and providing structured feedback to support model development and performance enhancement. Data Labeling Tasks Performed: Evaluated and rated AI-generated responses based on criteria such as accuracy, relevance, clarity, instruction-following, and overall quality. Identified factual errors, inconsistencies, and quality issues, conducted research and fact-checking when required, and provided detailed annotations and feedback according to project guidelines. Project Size: Worked on a large-scale AI training initiative involving the review and evaluation of numerous AI-generated responses across a variety of topics and domains. Consistently completed assigned tasks while meeting project deadlines and quality expectations. Quality Measures Adhered To: Followed detailed annotation guidelines, maintained consistency in evaluations, ensured accuracy through careful review and research, met quality assurance requirements, and adhered to established standards for objectivity, reliability, and data integrity.

2023 - Present

Education

Work History