Millikah P.

Key Skills

Software

Don't disclose

Top Subject Matter

AI data annotation content evaluation and quality assurance

Web research and data verification for AI annotation workflows

Cybersecurity foundations supporting AI/data verification competence

Top Data Types

Text

Computer Code Programming

Top Task Types

Question Answering

Freelancer Overview

AI Data Annotation Specialist (AI data evaluation/content review and quality assurance). Core strengths include Don't disclose. Education includes High School Diploma, Hez-Dike Secondary School (2019). AI-training focus includes data types such as Text, Computer Code, and Programming and labeling workflows including Evaluation, Rating, and Question Answering.

Labeling Experience

Completed cybersecurity coursework to support data verification and quality assurance

Don't disclose

Completed cybersecurity and programming-focused learning intended to strengthen technical capability for research and AI-related data work. Built practical understanding that supports verification and safe handling of technical materials. Used course content to improve troubleshooting and analytical thinking for annotation-related quality checks.•ISC2 Cybersecurity Course (Certificates of Completion)•Technical documentation and structured learning•Improved analytical/troubleshooting skills•Support for verification-oriented workflows

2026 - Present

AI Data Annotation / Web Research and Data Verification

Don't discloseTextQuestion Answering

Conducted web research and information verification activities to support AI annotation and data quality workflows. Leveraged AI-enabled question answering approaches to find, cross-check, and validate information. Ensured outputs matched source evidence and written guidelines for reliable labeled content.•Web Research (Claude Code)•Information verification for research outputs•Quality assurance via guideline-compliant checking•AI-assisted research and documentation practice

2026 - Present

AI Data Annotation Specialist (AI data evaluation/content review and quality assurance)

Don't discloseText

Performed content evaluation and quality assessment for AI data annotation tasks aligned to evaluation and rating workflows. Applied rating criteria to web research and content review activities using AI-assisted tools. Followed dataset guidelines and quality expectations to ensure consistent labeled outputs.•AI Data Annotation and Content Evaluation (Claude 101)•Content and quality verification using AI tools•Adherence to written guidelines and quality assurance criteria•Web research and documentation-based checking

2026 - Present

Education

Work History