Wisdom A.

Key Skills

Software

Other

Top Subject Matter

Language Domain Expertise

Nlp Domain Expertise

education/Math instruction

Top Data Types

Text

Audio

Document

Top Task Types

Classification

RLHF

Red Teaming

Entity (NER) Classification

Freelancer Overview

Peer Tutor (Mathematics Education) in Contract Review, Compliance, and Legal Research. Brings 3+ years of professional experience across complex professional workflows, research, and quality-focused execution. Core strengths include Other. Education includes Bachelor of Science, University of Benin (2024). AI-training focus includes data types such as Text and labeling workflows including Evaluation, Rating, and Classification.

Labeling Experience

Campus Ambassador & Team Lead, OneDosh (Fintech Platform) — 2024 to Present

OtherText

Evaluated team outreach accuracy, output quality, and completion against task expectations through structured weekly reporting. Produced and reviewed educational content on financial and blockchain topics with clarity and precision aligned to quality-assurance principles. • Quality assurance review for task outputs. • Consistency checks for rubric or guideline adherence. • Educational content precision for instructional datasets. • Weekly comparative evaluation reporting.

2024 - Present

Web3 Content Creator, CTNG Community — 2022 to Present

OtherText

Published fact-checked educational materials on blockchain, DeFi, and Web3 topics, verifying sources before publication. Wrote for beginner audiences, ensuring instructional clarity and correctness through careful review. • Source verification to ensure factual accuracy. • Instructional clarity checks for educational content. • Quality-oriented review prior to release. • Domain-focused rewriting for audience comprehension.

2022 - Present

AI Data Annotator & Prompt Engineer (Freelance) — 2022 to Present

OtherTextClassificationRLHF

Labeled and wrote AI training data for language models across creative writing, education, and technical domains while applying annotation guidelines precisely. Ranked and evaluated AI outputs for factual accuracy, tone, structure, and compliance with instructions, documenting reasoning for each judgment. Built adversarial prompts to surface weaknesses and generate edge-case examples for improved model robustness. • Text classification and categorization (sentiment, intent, topic). • Named entity recognition and entity labeling (people, locations, organizations, time). • RLHF preference labeling and reward-model style ranking. • Prompt + response evaluation and adversarial prompt construction for fine-tuning.

2022 - Present

Education

Work History