San D.

Key Skills

Software

Other

Top Subject Matter

Chemistry (analytical, organic synthesis, physical chemistry simulations)

Chemistry research datasets (molecular structures, experimental data)

Top Data Types

Text

Top Task Types

Prompt + Response Writing (SFT)

Entity (NER) Classification

Freelancer Overview

Freelance Chemistry Consultant (AI/LLM prompt development, response evaluation, and dataset annotation/validation). Brings 11+ years of professional experience across complex professional workflows, research, and quality-focused execution. Core strengths include Other. Education includes Bachelor of Science, University of Cincinnati (2016) and Doctor of Philosophy, University of Pittsburgh (2021). AI-training focus includes data types such as Text and labeling workflows including Prompt + Response Writing (SFT) and Entity (NER) Classification.

Labeling Experience

Freelance Chemistry Consultant (AI/LLM prompt development, response evaluation, and dataset annotation/validation)

OtherTextPrompt + Response Writing (SFT)

The role involved developing and refining prompts and evaluating AI-generated chemistry responses for quality and reliability. The work included structured review for factual accuracy, logical consistency, and bias as part of AI training or tutoring workflows. The consultant also applied detailed annotation standards to scientific datasets and training materials used for model improvement. • Prompt engineering for LLM training in chemistry domains • Evaluation/rating of AI outputs for hallucinations and reasoning errors • Validation of scientific accuracy and logical consistency • Application of annotation/QC standards to chemistry training data

2021 - Present

Teaching and Research Assistant — University of Pittsburgh (structured annotation, labeling, and validation of chemistry data)

OtherTextEntity (NER) Classification

The position included structured annotation and validation of scientific/experimental chemistry datasets and chemical information. The assistant labeled molecular structures and organized datasets with precision and consistency to support research reproducibility and documentation. This work functioned as data labeling and quality assurance for chemistry-related scientific inputs used in research workflows. • Annotated molecular structures and chemical datasets • Organized experimental data with labeling and validation • Ensured consistency and precision in scientific dataset annotations • Supported reproducible computational workflows and lab documentation

2016 - 2021

Education

Work History