Mhiz S.

Key Skills

Software

Appen

CVAT

Toloka

Top Subject Matter

AI training data

NLP linguistic datasets

text/media fact verification

Top Data Types

Text

Image

Audio

Top Task Types

RLHF

Object Detection

Text Generation

Question Answering

Text Summarization

Classification

Data Collection

Freelancer Overview

Freelance Data Labeling & Verification Specialist (Remote). Brings 3+ years of professional experience across complex professional workflows, research, and quality-focused execution. Core strengths include high-accuracy data classification, natural language processing (NLP) evaluation, and deep logical analysis. Education includes a Bachelor of Science in Education (Mathematics) from Kogi State University (2024). AI-training focus includes data types such as Text, Image, and Audio, with specialized expertise in Evaluation, Rating, and RLHF workflows.

Labeling Experience

Freelance Data Labeling & Verification Specialist (Remote)

OtherText

Provided high-volume data labeling, verification, and semantic evaluation for AI training datasets. Reviewed and audited AI-generated text and media against strict multi-point reference guidelines to identify hallucinations, bias, and logical errors. Annotated linguistic datasets by labeling parts of speech, sentiment, and intent to improve NLP model performance. • Text categorization and labeling following complex evolving instructions. • Semantic evaluations for consistency and guideline compliance. • Fact-checking and verification of AI-generated outputs. • Linguistic annotation (POS, sentiment analysis, intent classification).

2024 - Present

Mathematics Educator (NYSC)

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Developed structured frameworks for evaluating logical reasoning and identifying systematic errors in student problem-solving datasets. Organized and managed student performance records to track learning curves and pattern variations. Produced step-by-step instructional materials with strict structural formatting to support consistent evaluation criteria. • Labeled and categorized logical reasoning errors in datasets. • Managed and organized performance data for ongoing assessment. • Built structured evaluation frameworks and instructional materials. • Focused on correctness and logical clarity of responses.

2024 - 2025

Education

Work History