Macksunday Ayoga

Key Skills

Software

Labelbox

Mindrift

Snorkel AI

Top Subject Matter

No subject matter listed

Top Data Types

Audio

Computer Code Programming

Image

Text

Top Label Types

Entity Ner Classification

Segmentation

Classification

Text Generation

Transcription

Freelancer Overview

I am a data-driven professional with a strong background in mathematics, statistics, and data science, specializing in AI training data and annotation. My recent experience as a STEM AI Trainer involved meticulously labeling and validating advanced mathematics datasets, crafting rigorous proof-based prompts and responses, and ensuring that AI models accurately reflect real-world reasoning and problem-solving processes. I have extensive experience in data cleaning, quality assurance, and the use of LaTeX for precise mathematical formatting, as well as a proven ability to translate complex data into actionable insights across domains like finance, government statistics, and customer analytics. My focus is on maintaining high standards of accuracy and clarity in data labeling projects, enabling AI systems to deliver reliable, explainable outcomes.

Labeling Experience

multimodal Data Annotation & Quality Evaluation Invisible Technologies

LabelboxTextEntity Ner ClassificationSegmentation

Experienced in large-scale multimodal data annotation projects supporting the training and evaluation of Large Language Models (LLMs) and AI systems. Performed text classification, prompt response quality evaluation, sentiment labeling, entity tagging, image annotation, and multimodal alignment tasks according to detailed client guidelines. Annotated and reviewed thousands of data samples, achieving high accuracy and consistency. Applied quality control procedures, including peer review, gold-standard checks, and rubric-based scoring, to ensure dataset reliability. Worked with QA teams to resolve edge cases and improve labeling guidelines. Consistently met productivity and accuracy benchmarks in fast-paced production environments.

Experienced in large-scale multimodal data annotation projects supporting the training and evaluation of Large Language Models (LLMs) and AI systems. Performed text classification, prompt response quality evaluation, sentiment labeling, entity tagging, image annotation, and multimodal alignment tasks according to detailed client guidelines. Annotated and reviewed thousands of data samples, achieving high accuracy and consistency. Applied quality control procedures, including peer review, gold-standard checks, and rubric-based scoring, to ensure dataset reliability. Worked with QA teams to resolve edge cases and improve labeling guidelines. Consistently met productivity and accuracy benchmarks in fast-paced production environments.

2024 - 2025

Education

Work History