Muhammadbello I.

Key Skills

Software

OneForma

Appen

Top Subject Matter

NLP model output evaluation

search relevance

content quality (economics-informed judgment)

Top Data Types

Text

Document

Top Task Types

Data Collection

Transcription

Question Answering

Freelancer Overview

Freelance Data Annotator – AI Training Projects (NLP/Model Output Evaluation). Core strengths include OneForma, Appen, and Google Workspace (Docs. Education includes Master of Science, University of Ilorin (2024) and Bachelor of Science, University of Ilorin (2019). AI-training focus includes data types such as Text and Document and labeling workflows including Evaluation, Rating, and Data Collection.

Labeling Experience

Freelance Data Annotator – AI Training Projects (NLP/Model Output Evaluation)

OneFormaText

Reviewed and annotated text samples, search queries, and model-generated outputs using structured labeling frameworks and project-specific guidelines. Evaluated whether AI-generated content was accurate, relevant, and appropriate, applying domain-informed judgment for edge cases. Produced consistent quality decisions while meeting daily productivity and quality targets across multiple remote projects. • Reviewed and labeled search queries and AI responses • Applied rubrics and project guidelines to determine accuracy and relevance • Escalated ambiguous or out-of-scope samples to project managers • Collaborated remotely to clarify instructions and ensure consistency

2022 - Present

AI Data Evaluator – NLP & Search Relevance (Freelance)

AppenText

Performed search relevance rating, text classification, and model output comparison tasks for AI research labs and technology companies. Evaluated whether responses were accurate, helpful, and contextually appropriate using critical reasoning and guideline adherence. Documented annotation decisions clearly and consistently while participating in QA calibration activities based on feedback. • Completed search relevance ratings and text classification • Compared model outputs against expected criteria • Wrote reproducible justifications following structured rubrics • Participated in calibration to improve inter-annotator agreement

2021 - Present

Research Assistant (Intern), Department of Economics

DocumentData Collection

Assisted faculty researchers in collecting, cleaning, and categorizing economic survey data for policy analysis projects. Produced structured written summaries of findings, including data tables and citation-supported observations. Supported rigorous data handling by applying careful attention to detail across large volumes of structured materials. • Collected and cleaned economic survey datasets • Categorized structured survey data for policy research • Created written research summaries with tables • Supported analytical rigor and detail-oriented data processing

2023 - 2024

Education

Work History