Mercy M.

Key Skills

Software

Other

Top Subject Matter

ICT asset data quality assurance and structured categorisation

Training participation datasets and structured record tagging

Top Data Types

Text

Top Task Types

Classification

Freelancer Overview

ICT & Data Support Intern (MICDE) — Data validation and labeling standards. Brings 1+ years of professional experience across complex professional workflows, research, and quality-focused execution. Core strengths include Internal, Proprietary Tooling, and Other. Education includes Diploma in Information Communication Technology (ICT), Kiriri Women's University of Science and Technology (2026) and Certificate in Hospitality Management, Mahanaim College (2025). AI-training focus includes data types such as Text and labeling workflows including Classification.

Labeling Experience

Academic Data Projects (Kiriri Women’s University of Science and Technology) — data categorisation and structured tagging

OtherTextClassification

Entered, validated, and consistently categorised participation data across multiple Excel workbooks using uniform labeling conventions. Structured and tagged records in a library management system to support accurate retrieval and end-user display. Applied database normalisation and consistent field-level structuring in MySQL and SQLite to reinforce clean, well-labeled data for downstream systems. • Categorised and validated participation records with consistent labeling conventions • Implemented structured tagging/structuring in a Library Management System • Normalised and organised fields in MySQL/SQLite for reliable data usage • Ensured label consistency across hundreds of records for training-related datasets

2025 - 2026

ICT & Data Support Intern (MICDE) — Data validation and labeling standards

TextClassification

Validated and cleaned ICT asset records by applying consistent rules to catch, flag, and correct inaccurate or mislabeled entries. Conducted root-cause analysis on data inconsistencies across ICT asset registers to produce clean downstream datasets. Reviewed and proofread management reports to ensure accuracy before stakeholder submission. • Applied labeling conventions to identify and correct mislabeled ICT asset entries • Structured tagging and categorisation conventions for reliable querying and reporting • Reconciled records across registers to remove inconsistencies • Performed quality assurance checks at detail level (proofreading and accuracy validation)

2025 - 2025

Education

Work History