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Ebuka Umerah

Ebuka Umerah

Experienced Data Labeler for Video Annotation

USA flagAustin, Usa
$25.00/hrExpertAppenClickworkerData Annotation Tech

Key Skills

Software

AppenAppen
ClickworkerClickworker
Data Annotation TechData Annotation Tech
MindriftMindrift
OneFormaOneForma
TelusTelus
Scale AIScale AI

Top Subject Matter

No subject matter listed

Top Data Types

Computer Code ProgrammingComputer Code Programming
TextText
VideoVideo

Top Task Types

Data Collection
Evaluation Rating
Prompt Response Writing SFT
RLHF
Text Generation

Freelancer Overview

As an English Language Specialist with a PhD in English Literature and over six years of combined academic and industry experience, I bring a unique blend of linguistic expertise and practical application to AI training data. My recent freelance role as an AI Language Quality Trainer involved meticulously evaluating and correcting machine-generated English content for fluency, coherence, and factual accuracy. I actively contributed to the fine-tuning of AI language models by reviewing extensive datasets and precisely annotating nuanced language features, consistently ensuring AI output aligned with human linguistic standards. My qualifications are particularly well-suited for data annotation, emphasizing a deep understanding of linguistic principles, discourse analysis, and human-in-the-loop (HITL) processes. I possess a meticulous attention to detail crucial for maintaining data integrity and quality, and I am proficient with annotation platforms such as Mindrift, Outliernand LightTag. My academic background, coupled with hands-on experience in AI prompt evaluation and content review, sets me apart by enabling a comprehensive and nuanced approach to preparing high-quality training data for cutting-edge AI systems.

ExpertFrenchEnglish

Labeling Experience

Data Annotation Tech

Search Relevance and Query-Response Evaluation

Data Annotation TechTextEntity Ner ClassificationQuestion Answering
Assessed the relevance of search results to user queries and evaluated the quality of AI-generated answers to questions. This involved ranking responses based on accuracy, completeness, and helpfulness, and classifying queries by intent to improve search engine algorithms.

Assessed the relevance of search results to user queries and evaluated the quality of AI-generated answers to questions. This involved ranking responses based on accuracy, completeness, and helpfulness, and classifying queries by intent to improve search engine algorithms.

2023 - 2024
Appen

Sentiment Analysis and Content Moderation for Social Media

AppenTextClassification
Labeled social media comments and posts for sentiment (positive, negative, neutral, mixed) and identified specific entities (e.g., brand names, products, people). This project contributed to training models for automated content moderation and brand sentiment tracking, ensuring accurate categorization of user-generated content.

Labeled social media comments and posts for sentiment (positive, negative, neutral, mixed) and identified specific entities (e.g., brand names, products, people). This project contributed to training models for automated content moderation and brand sentiment tracking, ensuring accurate categorization of user-generated content.

2022 - 2023
Scale AI

Conversational AI Dialogue Evaluation & Refinement

Scale AITextText Generation
Evaluated and refined AI-generated dialogue for chatbots and virtual assistants. Tasks included assessing fluency, coherence, grammatical correctness, and factual accuracy of responses. I provided detailed feedback and re-wrote responses to align with specific linguistic and conversational guidelines, ensuring natural and effective human-AI interaction. This involved classifying intent, identifying emotional tone, and ensuring appropriate responses to user queries.

Evaluated and refined AI-generated dialogue for chatbots and virtual assistants. Tasks included assessing fluency, coherence, grammatical correctness, and factual accuracy of responses. I provided detailed feedback and re-wrote responses to align with specific linguistic and conversational guidelines, ensuring natural and effective human-AI interaction. This involved classifying intent, identifying emotional tone, and ensuring appropriate responses to user queries.

2020 - 2022

Education

U

University of Texas at Austin

Doctor of Philosophy, English Literature

Doctor of Philosophy
2020 - 2024
C

Columbia University

Master of Arts, English Language and Literature

Master of Arts
2018 - 2020

Work History

V

Various Data Annotation Clients (Freelance/Consultant)

AI Language Quality Specialist

Dallas
2024 - Present
A

Appen

Data Annotator

Ashburn
2022 - 2024