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dustintdn/README.md

Hi, I'm Dustin 👋

Data Scientist @ Aon | Quantitative Methods in the Social Sciences M.A., Columbia University

Welcome to my playground for exploring new project ideas and experiments! I work at the intersection of people analytics, applied ML, and causal inference - using data to answer questions about human behavior at scale. Currently building tools that bring LLMs into real-world workflows.

🚀 Featured Projects

Project Description
ai-citation-audit CLI tool measuring brand visibility across LLMs (ChatGPT, Claude, Perplexity)
llm-engagement-summarizer LLM-powered theme extraction from employee engagement surveys
ai-resolution-quality Causal inference (PSM + DiD) on AI-assisted customer support outcomes
mmm-budget-optimization Marketing Mix Model (MMM) to optimize budget allocation for paid media
ab-test-framework Reusable Python framework for A/B test analysis

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  1. ai-citation-audit ai-citation-audit Public

    CLI tool for auditing brand visibility across LLMs - queries ChatGPT, Claude, and Perplexity with structured prompt batteries and outputs citation rate, position, and sentiment by competitor

    Python

  2. llm-engagement-summarizer llm-engagement-summarizer Public

    Analyzing employee engagement survey comments using LLM-powered topic/theme summarization

    Python

  3. ai-resolution-quality ai-resolution-quality Public

    Causal inference pipeline (PSM + DiD) estimating the effect of AI assistance on customer-support resolution quality

    Jupyter Notebook

  4. rag-eval-pipeline rag-eval-pipeline Public

    A production-style RAG pipeline that ingests documents, answers questions, and evaluates itself on retrieval and generation quality with: async jobs, streaming, hybrid retrieval, a Cohere reranker,…

    Python

  5. lm-eval-demo lm-eval-demo Public

    Benchmarking SLMs on structured extraction, RAG Q&A, intent classification, and latency

    Jupyter Notebook

  6. mmm-budget-optimization mmm-budget-optimization Public

    Marketing Mix Model that quantifies channel contribution and optimizes budget allocation across paid media using PyMC.

    Jupyter Notebook