Precious I.

Key Skills

Software

Don't disclose

Micro1

Data Annotation Tech

Top Subject Matter

Healthcare / Medical and Microbiology data review

Medical research datasets quality review (healthcare/microbiology)

AI prompt evaluation for healthcare / medical writing quality

Top Data Types

Document

Text

Image

Top Task Types

Diagnosis

Prompt + Response Writing (SFT)

Question Answering

Text Generation

Freelancer Overview

Medical Doctor – medical data interpretation and QA support. Brings 3+ years of professional experience across legal operations, contract review, compliance, and structured analysis. Core strengths include Don't disclose, Google Docs, and Google Sheets. Education includes Bachelor of Medicine, Bachelor of Surgery, University of Nigeria, Nsukka (2023). AI-training focus includes data types such as Medical, DICOM, and Document and labeling workflows including Diagnosis, Evaluation, and Rating.

Labeling Experience

AI & Data Evaluation Experience – prompt and response quality review

TextPrompt + Response Writing (SFT)

Evaluated written responses for factual accuracy, clarity, and logical consistency to improve AI-assisted healthcare content quality. Assisted in refining healthcare-related prompts and improving content through careful review and iterative adjustments. Applied medical domain understanding to support prompt evaluation workflows and ensure outputs align with correct clinical reasoning. • Assessed AI-generated or written responses for factual correctness • Evaluated clarity and logical consistency of healthcare outputs • Refined healthcare-related prompts to improve answer quality • Supported AI-assisted workflows using medical expertise and quality checks

2024 - Present

Medical Doctor – medical data interpretation and QA support

Don't discloseDiagnosis

Supported AI/data-quality efforts by interpreting and reviewing healthcare information for accuracy and consistency in fast-paced clinical documentation. Focused on identifying errors or inconsistencies in clinical and laboratory-derived content to maintain high annotation/label quality standards. Contributed evidence-based context to help ensure labeled outputs reflect correct medical reasoning and terminology. • Reviewed medical terminology, clinical notes, and healthcare-related information for accuracy • Checked consistency and quality of clinical and microbiology information • Applied critical thinking to flag inconsistencies in patient-related datasets • Maintained confidentiality while handling sensitive medical data

2024 - Present

Research Assistant / Medical Research Contributor – dataset QA and annotation support

Document

Performed dataset and research content quality assurance by reviewing healthcare-related datasets for consistency, accuracy, and readiness for downstream AI-assisted use. Conducted literature reviews and summarized scientific findings while verifying medical and microbiology information to improve data reliability. Prepared structured research documentation and reports with attention to factual correctness and clarity for technical stakeholders. • Verified dataset consistency and quality assurance checks • Summarized scientific literature findings for healthcare projects • Supported organization and verification of medical and microbiology research data • Produced reports, presentations, and structured documentation under deadlines

2024 - 2025

Education

Work History