D'Von P.

Key Skills

Software

Other

Internal/Proprietary Tooling

Top Subject Matter

Healthcare (telehealth, clinical documentation, EMR-adjacent records)

Healthcare (nursing & rehabilitation documentation, patient records)

Finance/compliance data (for evaluation and accuracy disciplines applicable to labeling QA)

Top Data Types

Document

Text

Medical Dicom

Top Task Types

Data Collection

Freelancer Overview

Clinical Data Specialist & Telehealth Field Coordinator — Total Care 2 U (TC2U). Brings 5+ years of professional experience across complex professional workflows, research, and quality-focused execution. Core strengths include Other. Education includes Bachelor of Computer Science, Baylor University (2027) and Associate of Communications, Tarrant County College (2022). AI-training focus includes data types such as Medical, DICOM, and Document and labeling workflows including Evaluation and Rating.

Labeling Experience

Clinical Data Specialist & Telehealth Field Coordinator — Total Care 2 U (TC2U)

Other

Serves as a clinical evaluation specialist by reviewing patient health histories and provider notes for completeness, accuracy, and clinical plausibility, analogous to scoring AI outputs against rubric criteria. Applies strict clinical documentation standards across concurrent cases to ensure consistent quality under compliance constraints. Uses structured communication to help align complex clinical details with remote providers and evaluation requirements. • Completeness and correctness checks against clinical expectations • Clinical plausibility assessment for safety and nuance • Consistent rubric-following habits across multiple simultaneous cases • Structured summaries to support conversational/medical AI training context

2025 - Present

Patient Data Coordinator & Documentation Specialist — The Hills Nursing & Rehabilitation

Other

Maintains HIPAA-compliant records across high-volume patient populations while applying consistent standards to varied real-world inputs, similar to ensuring labeling consistency across a dataset. Identifies patterns and discrepancies in patient data and escalates concerns, aligning with quality assurance and anomaly detection used in labeling QA. Supports accurate downstream interpretation through careful documentation and structured intake. • Pattern identification and discrepancy detection in high-volume records • Escalation of suspected errors or out-of-distribution cases • Consistent application of compliance and documentation standards • QA-style review mindset for varied and noisy inputs

2023 - 2025

Financial Data Specialist & Client Account Manager — U.S. Bank

OtherDocument

Processes high-volume financial data with strict compliance protocols and zero tolerance for error, building accuracy habits relevant to data labeling and review work. Applies policy standards across daily interactions and escalates edge cases, similar to handling ambiguous samples during annotation QA. Demonstrates consistent guideline adherence and careful verification of inputs before downstream use. • High-volume compliance-driven accuracy checks • Escalation of edge cases and policy exceptions • Consistent application of standards under time constraints • Judgment for ambiguous or high-risk cases

2022 - 2023

Education

Work History