Abass R.

Key Skills

Software

Other

Top Subject Matter

AI training quality assurance and content moderation (via data ethics and labeling standards)

Dataset quality control

Classification Domain Expertise

Top Data Types

Document

Image

Text

Top Task Types

Fine-tuning

Freelancer Overview

ICT Vocational Instructor (Digital ethics, quality assurance, and data entry supervision) at Modeke Igboho Development F. Brings 8+ years of professional experience across complex professional workflows, research, and quality-focused execution. Core strengths include Other, Microsoft Excel, and Python. Education includes National Diploma, Igbehin Adun College (2016) and Higher National Diploma, Waziri Umaru Federal Polytechnic (2019). AI-training focus includes data types such as Document, Computer Code, and Programming and labeling workflows including Evaluation, Rating, and Fine-tuning.

Labeling Experience

ICT Vocational Instructor (Digital ethics, quality assurance, and data entry supervision) at Modeke Igboho Development Foundation (MIDF)

OtherDocument

He supervised student practice on precise data entry and document formatting to improve dataset quality. He also taught digital ethics and quality assurance concepts relevant to content moderation and RLHF-style feedback. His instruction supports consistent labeling standards and logical checks for high-integrity AI training data. • Supervised 50+ learners in accurate data entry and formatting • Emphasized error-free, quality-first data input practices • Taught online safety, data ethics, and critical logical thinking • Applied training concepts to content moderation and RLHF readiness

2025 - Present

Industrial Learning & Development Assistant (NYSC) at Lafarge Africa PLC

Document

He performed data collation and quality control for nationwide training assessment databases, ensuring dataset integrity. He reviewed, edited, and classified multi-location training imagery and assets to maintain alignment with presentation standards. He also managed an asset database by tracking entries and correcting discrepancies, supporting clean structured records for analytics and potential AI dataset preparation. • Collated training assessment databases in MS Excel with 100% integrity • Conducted visual auditing by reviewing and classifying training imagery/assets • Managed facilities asset database and fixed discrepancies • Applied QA-focused review steps to reduce data-entry errors

2023 - 2024

AI Training & Data Labeling Simulations / Independent Study

Fine-tuning

He conducted independent AI training simulations focused on structuring and cleansing unstructured data for machine learning-ready datasets. He performed prompt engineering and evaluated LLM outputs for factual accuracy, formatting alignment, and safety guidance compliance. These activities align with building training corpora and running evaluation checks typical for supervised fine-tuning and LLM dataset preparation. • Used Python and MySQL to sort, clean, and structure unstructured data • Prepared simulated training sets for machine learning models • Evaluated LLM outputs for factual accuracy and formatting alignment • Assessed safety guideline compliance as part of prompt + response evaluation

Not specified

Education

Work History