RLHF Evaluation for Finance Model Responses
Compared and ranked AI responses based on accuracy, instruction-following, reasoning quality, source usage, calculation correctness, hallucination risk, and professional finance style output.
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I have experience in AI training data and data labeling across finance, investment banking, private equity, financial modeling, investment research, and financial planning tasks. My work includes prompt response writing / SFT, RLHF response evaluation, rubric writing, golden deliverable creation, source-grounding review, failure testing, model comparison and ranking, spreadsheet annotation, financial document reasoning, and image annotation for slide decks. I have created high-quality reference responses, evaluated AI-generated outputs, built grading rubrics, reviewed financial models, and identified hallucinations, calculation errors, unsupported assumptions, weak reasoning, and instruction-following issues. Education includes Bachelor of Science in Finance, University of Louisiana at Lafayette (2024).
Compared and ranked AI responses based on accuracy, instruction-following, reasoning quality, source usage, calculation correctness, hallucination risk, and professional finance style output.
Created objective grading rubrics, golden deliverables, and prompts that stump models for AI responses involving DCFs, LBOs, merger models, accretion/dilution analysis, operating models, transaction summaries, and valuation write-ups.
I focused on creating accurate, well-structured answers that demonstrated strong financial reasoning, correct calculations, and professional client-ready communication as well as building a rubric for a correct response.
Bachelor of Science in Business Administration, Finance
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