Predictive Operations Control Center on Shiny Dashboards
Harnessing advanced R and ML analytics, this project delivers an integrated Demand Forecasting Dashboard and Predictive Pricing Tool to optimize sales, inventory, and strategic …
Professional Summary
I am a Data Scientist and Operations Research Analyst with over a decade of experience bridging the gap between rigorous statistical theory and frontier-tier AI implementation. My career has been defined by high-stakes environments—from conducting $20B+ cost assessments for the Air Force to building NLP-driven clustering models for brands like Chipotle.
I specialize in creating autonomous, self-improving systems that drive measurable business value:
Agentic AI & RAG: Architecting multi-agent systems with LangGraph, CrewAI, and LangChain to solve complex, unstructured enterprise problems.
Predictive Modeling: Developing high-accuracy models (85%+) for churn, demand forecasting, and cost analysis using Python and R.
Strategic Leadership: Leading $20B+ program assessments (TS/SCI Cleared) and mentoring data teams in SaaS and Government sectors.
Full-Stack Deployment: Building production-grade data tools and interactive dashboards using Streamlit, R-Shiny, and Databricks.
I thrive at the intersection of predictive analytics and agentic workflows, turning raw data into strategic, autonomous advantages.
Education
MS Statistics
California State University, Fullerton
BA Business Economics
University of California, Riverside
Interests
Experimental Design
Data Visualization
Product Development
Large Language Models
Recent Blogs
R-Powered Analytical Reporting: Sales, Product Pricing, and Customer Segmentation
R-Markdown dashboards and machine learning models deliver actionable sales insights and predict optimal pricing for a bicycle company's new product line.
Bank Customer Churn EDA and Prediction Part 1
Predicting Churn, Securing Loyalty: Modeling Bank Customer Retention.