Joelvalentine Okwunna

Key Skills

Software

Other

Data Annotation Tech

Top Subject Matter

Conversational AI/Chatbots

Fintech Chatbot/Conversational AI

LLM Text Generation/Conversational AI

Top Data Types

Text

Document

Image

Top Task Types

Question Answering

Text Summarization

Classification

Freelancer Overview

AI Chatbot Quality Analyst (Contract). Brings 2+ years of professional experience across legal operations, contract review, compliance, and structured analysis. Core strengths include Prolific, Other, and Data Annotation Tech. Education includes Bachelor of Arts, Nnamdi Azikiwe University (2024) and Master of Science, Teesside University (2025). AI-training focus includes data types such as Text and labeling workflows including Evaluation and Rating.

Labeling Experience

AI Chatbot Quality Analyst (Contract)

Text

Evaluated large language model (LLM) chatbots for context retention, coherence, and tone consistency over multi-turn conversations. Designed adversarial and stress-test dialogue scenarios to reveal model failure modes and documented failure patterns using structured rubrics. Rated chatbot responses using RLHF-aligned human preference frameworks and contributed to developing a reusable QA template library for AI evaluations. • Conducted structured evaluations across 30+ topic domains • Designed and executed 150+ dialogue test scenarios • Documented failure patterns for feedback to product teams • Rated chatbot outputs using RLHF frameworks

Evaluated large language model (LLM) chatbots for context retention, coherence, and tone consistency over multi-turn conversations. Designed adversarial and stress-test dialogue scenarios to reveal model failure modes and documented failure patterns using structured rubrics. Rated chatbot responses using RLHF-aligned human preference frameworks and contributed to developing a reusable QA template library for AI evaluations. • Conducted structured evaluations across 30+ topic domains • Designed and executed 150+ dialogue test scenarios • Documented failure patterns for feedback to product teams • Rated chatbot outputs using RLHF frameworks

2024 - Present

UX Researcher & Dialogue Tester (Freelance)

OtherText

Performed usability and dialogue flow testing on a customer-service chatbot for a fintech firm, focusing on annotation of conversation breakdowns and context loss. Developed a dialogue audit framework and collected structured feedback using NPS and custom rubrics. Produced UX reports mapping observed failures to NLP model issues, aiding in product improvements. • Identified 22 conversation breakdowns via structured annotation • Developed audit framework to track context loss and reduce repeat questions • Conducted qualitative interviews and collected annotated feedback • Presented findings to the product team for sprint prioritization

Performed usability and dialogue flow testing on a customer-service chatbot for a fintech firm, focusing on annotation of conversation breakdowns and context loss. Developed a dialogue audit framework and collected structured feedback using NPS and custom rubrics. Produced UX reports mapping observed failures to NLP model issues, aiding in product improvements. • Identified 22 conversation breakdowns via structured annotation • Developed audit framework to track context loss and reduce repeat questions • Conducted qualitative interviews and collected annotated feedback • Presented findings to the product team for sprint prioritization

2023 - 2024

AI Content Evaluator & Prompt Engineer (Part-time)

Data Annotation TechText

Evaluated AI-generated text samples for accuracy, consistency, and instruction-following quality using detailed rubrics. Conducted red-teaming of AI systems and provided highly-structured written feedback for model fine-tuning. Applied philosophical analysis to assess argument coherence for prompt-based outputs. • Assessed 500+ AI text outputs for quality and accuracy • Performed prompt engineering to test model limitations • Delivered feedback with actionable recommendations • Achieved a 97% supervisor approval rate on evaluations

Evaluated AI-generated text samples for accuracy, consistency, and instruction-following quality using detailed rubrics. Conducted red-teaming of AI systems and provided highly-structured written feedback for model fine-tuning. Applied philosophical analysis to assess argument coherence for prompt-based outputs. • Assessed 500+ AI text outputs for quality and accuracy • Performed prompt engineering to test model limitations • Delivered feedback with actionable recommendations • Achieved a 97% supervisor approval rate on evaluations

2023 - 2023

Education

Work History