Samuel O.

Key Skills

Software

Label Studio

Anno-Mage

Labelbox

Top Subject Matter

AI training data labeling

response evaluation

content moderation

Top Data Types

Text

Document

Image

Top Task Types

Prompt + Response Writing (SFT)

Bounding Box

Entity (NER) Classification

Freelancer Overview

AI Data Annotation & Evaluation (Self-Directed / Freelance, Remote). Brings 3+ years of professional experience across legal operations, contract review, compliance, and structured analysis. Core strengths include Other. Education includes Bachelor of Science, Federal University Oye Ekiti (FUOYE) (2020). AI-training focus includes data types such as Text and labeling workflows including Evaluation, Rating, and Prompt + Response Writing (SFT).

Labeling Experience

Email Copywriter (Freelance, Remote, Ongoing)

OtherTextPrompt + Response Writing (SFT)

Created and refined written email content for promotional campaigns, newsletters, and outreach sequences with an emphasis on clarity, grammar, and audience-appropriate messaging. Edited and proofread drafts to ensure consistent tone and brand alignment across client deliverables. Although primarily copywriting, these tasks involved structured text creation and quality checks aligned with language production and evaluation workflows. • Wrote persuasive email sequences for different audiences • Edited/proofread content for grammatical accuracy and clarity • Adapted tone and messaging based on audience targeting requirements • Ensured consistency with brand guidelines and campaign objectives

2025 - Present

AI Data Annotation & Evaluation (Self-Directed / Freelance, Remote)

OtherText

Independently annotated and labeled text datasets to support AI model training for tasks such as text classification, intent recognition, and conversational AI. Evaluated AI-generated responses for accuracy, fluency, tone, and compliance with dataset guidelines while performing prompt testing to assess reasoning and language quality. Applied content moderation principles and fact-checking/web research to flag low-quality or inappropriate outputs and validate information accuracy in the training data. • Labeled categories for text classification and intent recognition • Assessed response quality using rubric-style criteria (accuracy, fluency, tone, guideline adherence) • Conducted conversational AI testing through prompt interactions • Flagged/categorized inappropriate or low-quality outputs and validated facts via web research

2025 - Present

Education

Work History