John Okpa

Key Skills

Software

Appen

Micro1

Telus

Remotasks

Mercor

Top Subject Matter

General Visual Content for AI Training

Data annotation/Labeling/Transcription

Regulatory Compliance & Risk Analysis

Top Data Types

Image

Text

Document

Top Task Types

Classification

Transcription

Evaluation Rating

Question Answering

Text Generation

Data Collection

Segmentation

Text Summarization

Fine Tuning

Freelancer Overview

Over the past year, I've been working as a Data Annotation & Evaluation Specialist at Appen, where I've gotten pretty comfortable with the ins and outs of preparing training data for AI models. My day-to-day involves about eight hours of hands-on labeling and annotation, which has really trained me to stay focused for long stretches without letting quality slip. I've learned to follow detailed guidelines closely—not just skimming them but really making sure each tag is accurate and consistent, because even small mistakes can throw off an AI's performance. What I think makes me stand out is how I've picked up a solid QA mindset along the way. I don't just label and move on—I double-check data for correctness, structure, and relevance, almost like I'm auditing my own work. That habit of validating outputs is something I see fitting perfectly with roles that ask for evaluating AI-generated content. Between hitting volume targets, keeping quality high, and building my own quality checks into the workflow, I've gotten good at handling large-scale datasets without cutting corners.

Labeling Experience

Data Annotation & Evaluation Specialist — Appen

AppenImageClassification

As a Data Annotation & Evaluation Specialist at Appen, I performed daily data annotation and labeling of images and short video clips for AI training datasets. I followed detailed annotation guidelines to ensure precision, consistency, and high data quality across all assigned tasks. My work involved validating AI-generated data outputs and maintaining quality benchmarks in a remote, independent setting. • Labeled high-volume image and video datasets using provided annotation rubrics. • Conducted accuracy checks and data validation for AI-generated outputs. • Developed agile proficiency with quality assurance workflows. • Ensured sustained 8-hour daily focus to meet strict project targets.

As a Data Annotation & Evaluation Specialist at Appen, I performed daily data annotation and labeling of images and short video clips for AI training datasets. I followed detailed annotation guidelines to ensure precision, consistency, and high data quality across all assigned tasks. My work involved validating AI-generated data outputs and maintaining quality benchmarks in a remote, independent setting. • Labeled high-volume image and video datasets using provided annotation rubrics. • Conducted accuracy checks and data validation for AI-generated outputs. • Developed agile proficiency with quality assurance workflows. • Ensured sustained 8-hour daily focus to meet strict project targets.

2025 - 2025

Education

Work History