Aleksandra Z.

Key Skills

Software

Snorkel AI

Top Subject Matter

Healthcare AI

Clinical symptom assessment and medical reasoning

Nursing

Top Data Types

Document

Video

Text

Top Task Types

Question Answering

Transcription

Data Collection

Freelancer Overview

Registered Nurse with acute care and healthcare AI review experience specializing in clinical reasoning evaluation, symptom assessment, medical documentation review, and evidence-based healthcare analysis. I currently work as a Nurse Contributor and Reviewer for Snorkel AI, where I review and evaluate healthcare-related datasets for clinical accuracy, symptom identification, documentation consistency, and medical reasoning quality to support AI model development and quality assurance initiatives. I was promoted to Reviewer for Project Harborlight within my first month due to strong analytical skills, attention to detail, and ability to identify inconsistencies in clinical interpretation and reasoning workflows. In addition to my AI review experience, I bring over four years of bedside nursing experience in high-acuity progressive care settings, allowing me to apply real-world clinical judgment, risk assessment, and evidence-based decision-making to structured review tasks. My background includes complex patient assessment, interdisciplinary collaboration, chart review, quality improvement initiatives, and compliance-focused documentation practices. I hold active PCCN and SCRN certifications and am highly comfortable evaluating diagnostic reasoning, treatment planning, guideline concordance, and patient safety considerations within remote, documentation-heavy healthcare review environments.

Labeling Experience

Nurse Contributor, Healthcare AI Reviewer (Independent Contractor) — Snorkel AI (Remote)

Snorkel AIDocument

Reviewed healthcare-related datasets to assess clinical accuracy, evidence-based reasoning, and documentation consistency for AI model development. Evaluated symptom identification and appropriate symptom interpretation to ensure medically accurate clinical decision-support reasoning. Conducted quality control through remote cross-functional review workflows aligned with evidence-based healthcare practices. • Clinical data annotation and symptom assessment review • Evidence-based medical reasoning and documentation consistency checking • Quality control to ensure reliable clinical decision-support outputs • Promotion within the first month to Reviewer for Project Harborlight

2026 - Present

Education

Work History