Warner Carnero

Key Skills

Software

Data Annotation Tech

Top Subject Matter

No subject matter listed

Top Data Types

Computer Code Programming

Document

Image

Text

Top Label Types

Computer Programming Coding

Prompt Response Writing SFT

Relationship

Freelancer Overview

I have a strong background in data annotation and AI training data, particularly within the scientific and chemistry domains. My experience as a Chemistry AI Tutor previously at DataAnnotation involved designing weighted rubrics and prompts to introduce challenging edge cases, training AI models to interpret complex figures and diagrams from chemistry publications, and ranking model responses for accuracy and instruction-following. I am skilled in Python, Linux, and a range of computational and data analysis tools for molecular dynamics simulations, and have hands-on experience developing and applying statistical and computational models to large datasets. With my background, I have assisted in many chemistry and STEM projects towards improving AI model understanding and interpretation of datasets in high impact publications and datasets generated in computational chemistry research.

Labeling Experience

Chemistry AI Tutor

Data Annotation TechDocumentPrompt Response Writing SFT

The project focused on developing challenging system/user prompts to be able train AI models to be able to parse, interpret datasets/figures, and be able to apply theoretical quantum mechanical derivations from provided documents towards cases that challenge AI model understanding of the document. From this, I was able to guide and improve model understanding for various topics and research problems typically expected in higher education within STEM.

The project focused on developing challenging system/user prompts to be able train AI models to be able to parse, interpret datasets/figures, and be able to apply theoretical quantum mechanical derivations from provided documents towards cases that challenge AI model understanding of the document. From this, I was able to guide and improve model understanding for various topics and research problems typically expected in higher education within STEM.

2025 - 2025

Education

Work History