Rike Odubawo

Key Skills

Software

Mercor

Top Subject Matter

No subject matter listed

Top Data Types

Image

Text

Video

Top Label Types

Bounding Box

Classification

Evaluation Rating

Freelancer Overview

I bring a unique blend of expertise in financial crime investigation and hands-on AI data annotation, with direct experience labeling, classifying, and evaluating data for large language model (LLM) training. My background includes annotating and fact-checking AI-generated outputs across financial, legal, and general-knowledge domains, where I consistently apply advanced web research, intent analysis, and structured feedback to improve model accuracy, safety, and bias mitigation. I have a deep understanding of prompt engineering, RLHF, and responsible AI practices, and I leverage my analytical skills and attention to detail to deliver high-quality, domain-specific annotations—especially in compliance, fraud detection, and regulatory content. My cross-disciplinary approach ensures that my data labeling work reflects real-world complexity and supports robust AI system development.

Labeling Experience

AI Data Annotation & LLM Evaluation Financial crime Domain

MercorImageBounding BoxClassification

Performed professional data annotation and LLM evaluation for AI model training across financial, legal, and general-knowledge domains. Tasks included evaluating model responses for accuracy, factual correctness, intent alignment, tone, and bias. Conducted image-based evaluations including photorealism assessment, furniture removal verification, bounding box annotation, and sketch-to-photo conversion quality review. Applied advanced fact-checking and OSINT methodologies to verify AI-generated content. Leveraged domain expertise in financial crime compliance to provide nuanced, high-quality annotations reflecting real-world regulatory complexity.

Performed professional data annotation and LLM evaluation for AI model training across financial, legal, and general-knowledge domains. Tasks included evaluating model responses for accuracy, factual correctness, intent alignment, tone, and bias. Conducted image-based evaluations including photorealism assessment, furniture removal verification, bounding box annotation, and sketch-to-photo conversion quality review. Applied advanced fact-checking and OSINT methodologies to verify AI-generated content. Leveraged domain expertise in financial crime compliance to provide nuanced, high-quality annotations reflecting real-world regulatory complexity.

2024 - 2025

Education

Work History