Henry Q.

Key Skills

Software

Other

Mercor

Top Subject Matter

Financial Advisory/Investment

Wealth Management

Behavioral Finance

Top Data Types

Text

Document

Top Task Types

Prompt + Response Writing (SFT)

Question Answering

Evaluation/Rating

Freelancer Overview

With over two decades of experience, I am a seasoned financial professional strategically positioned at the exciting intersection of finance and artificial intelligence (AI). I currently serve as a Finance and Investment Domain Expert, where my primary focus is training and refining top-tier Large Language Models (LLMs). In this capacity, I function as a financial prompt engineer, leveraging my deep domain knowledge to bridge the gap between complex financial realm and generative AI's capabilities. My work ensures these advanced AI systems produce outputs that are not only coherent but also analytically rigorous, contextually accurate, financially sound, humanistically conscientious, and ultimately shaping the next generation of intelligent tools for the finance industry. My expertise is grounded in a robust foundation built at some of the world's most respected financial institutions, including The Vanguard Group, Deutsche Bank, Merrill Lynch, and Bank of America. This experience provides the critical real-world knowledge in investment management, capital markets, risk analytics, and wealth management that I use to train AI models effectively. Education includes Master of Science, Simon Graduate School of Business Administration, University of Rochester and Master of Science, Rochester Institute of Technology. AI-training focus includes data types such as Text and labeling workflows including Prompt + Response Writing (SFT).

Labeling Experience

Financial Prompt Writer, Freelance

OtherTextPrompt + Response Writing (SFT)

As a freelance Financial Prompt Writer, I designed prompts to train large language models for financial advisory tasks. My work included developing comprehensive rubrics to evaluate LLM outputs in complex financial domains. This involved leveraging domain expertise to teach AI on portfolio construction, asset allocation, and risk management. • Designed reasoning-intensive prompt datasets for LLM training in finance • Drafted detailed evaluation rubrics and performance criteria for AI assessment • Focused on goals-based portfolio construction and related financial planning topics • Provided domain-expert feedback to optimize LLM accuracy and relevance

2025 - Present

Education

Work History