Chukwunonso O.

Key Skills

Software

Don't disclose

Toloka

Labelbox

Label Studio

Scale AI

CVAT

Top Subject Matter

Machine learning dataset enrichment and RLHF evaluation for language and audio tasks

Dataset workflow tooling for annotation systems and structured data validation

Public health survey dataset preparation and structured data curation

Top Data Types

Audio

Text

Document

Top Task Types

Transcription

Data Collection

Freelancer Overview

Remote Data Annotation & Audio Transcription Specialist — Freelance (Contract Remote). Brings 3+ years of professional experience across legal operations, contract review, compliance, and structured analysis. Core strengths include Don't disclose, Git, and GitHub. Education includes Bachelor of Technology, Federal University of Technology, Owerri (FUTO) (2027). AI-training focus includes data types such as Audio, Computer Code, and Programming and labeling workflows including Transcription, Computer Programming, and Coding.

Labeling Experience

Technical Data Assistant & Front-End Developer — Freelance / Open-Source (Remote)

Managed technical data workflows to support labeling-related datasets and quality checks, including maintaining version control and structured data artifacts. Implemented front-end logic and validations that ensure data entry interfaces preserve structural integrity of labeled/annotated outputs. Analyzed syntax defects within localized data arrays to improve troubleshooting performance and enhance script runtime predictability during dataset processing. • Version-controlled data workflow management using Git/GitHub • Structured JSON handling to maintain consistent annotation artifacts • Front-end validation logic for reliable structured outputs • Debugging of array syntax defects affecting dataset ingestion

2024 - Present

Remote Data Annotation & Audio Transcription Specialist — Freelance (Contract Remote)

Don't discloseAudioTranscription

Performed high-volume multi-speaker audio transcription and maintained transcript word-error-rate (WER) below 2% across varying acoustic qualities and accents. Annotated, labeled, and segmented text, audio, and visual data blocks using complex taxonomy criteria to improve machine learning model baseline metrics. Conducted Reinforcement Learning from Human Feedback (RLHF) audits by evaluating model-generated outputs for factual consistency, prompt alignment, structure, and safe policy guardrails. • Multi-speaker transcription quality control with WER KPI tracking • Text/audio/visual block annotation, labeling, and segmentation • RLHF case auditing for factuality, alignment, and safety compliance • Identification of ambiguous edge cases and documentation of guideline anomalies

2024 - Present

Data Records Assistant — Public Health Survey Projects (Academic)

Don't discloseData Collection

Supervised cleansing, structured categorization, and entry of field public health survey outcomes into centralized research tables with strict data privacy compliance. Identified and corrected reporting variance patterns within multi-tier demographic datasets to boost downstream metric analytics reliability. Ensured survey data was prepared in a consistent format suitable for later analysis and model-related evaluation. • Data cleansing and structured categorization for survey outcomes • Privacy-compliant entry into centralized research tables • Variance detection and correction across demographic strata • Preparing categorized records for downstream analytics

2025 - 2025

Education

Work History