Rebecca Z.

Key Skills

Software

Other

Top Subject Matter

Pharmaceutical Market Intelligence, Healthcare & Clinical Research, Epidemiology & Biostatistics

Data Science & Statistical Modelling

Bilingual Content Evaluation (English/Mandarin)

Top Data Types

Text

Document

Top Task Types

Classification

Point/Key Point

Evaluation/Rating

Computer Programming/Coding

Freelancer Overview

I have direct experience building AI-powered research tools: at IQVIA, I independently developed an automated workflow integrating LLM-based semantic coding, data cleaning pipelines, and dashboard generation — designed for real consulting workflows. I am familiar with prompt engineering, evaluating model responses for logical consistency and domain accuracy, and translating complex clinical or statistical content into clear, well-structured outputs. I approach AI evaluation tasks with both scientific rigour and practical awareness of how research findings are applied in real-world healthcare decision-making. Education includes Master of Science, National University of Singapore (2024) and Bachelor of Engineering, Tianjin University of Commerce (2024). AI-training focus includes data types such as Text and labeling workflows including Classification.

Labeling Experience

AI-powered research workflow intern (Text labeling and semantic coding)

TextClassification

Developed and implemented an AI-powered research workflow tool to automate data cleaning and semantic coding of open-ended pharmaceutical responses. The workflow included LLM-assisted semantic analysis and AI-driven dashboard generation for actionable insights. Responsible for label design and process optimization to enhance consultant usability and quantitative data analysis accuracy. • Automated semantic classification of open-ended text responses in pharmaceutical primary research projects. • Utilized LLM and internal/proprietary tools for high-quality research data labeling. • Designed and refined semantic labels for pharma context and client-facing deliverables. • Ensured integration of labeled outputs into quantitative reporting pipelines.

2025 - 2026

Education

Work History