Diego O’Hurtado

Architected and deployed a production-grade multi-agent IVR platform for CVS MinuteClinic using LangGraph StateGraph, enabling coordinated agent orchestration to resolve multiple patient intents within a single conversation. Built and launched LocatorAgent using Mistral and LangGraph, designing deterministic middleware that reduced response latency by 45% and LLM token consumption by 60%, enabling

Boosted Revenue per Click (RPC) by 5% by modernizing keyword matching with a production grade RAG system. Architected a Bi-Encoder retrieval layer indexed via FAISS to capture semantic user intent at millisecond latency. Engineered a Multimodal Recommendation System utilizing Computer Vision (CLIP) to predict high-converting image-keyword pairings, and drove an 8% uplift in Advertiser ROI by engin

Achieved a 10% increase in Click-Through Rate (CTR) by engineering a Learning-to-Rank objective within XGBoost, optimizing product ranking across billions of historical transactions. Increased Cross-Selling Recall@K by 25% by deploying an ML Ranking architecture that fuses user history and item features to solve the cold-start problem in recommendations, and enhanced recommendation coverage by dev

Optimized fleet utilization (Backhaul Discovery) by 5% by designing a hybrid framework merging LightGBM with Lag Features for demand forecasting and Linear Programming for route optimization. Improved operational efficiency by 30% across North American logistics networks by deploying predictive analytics for resource planning, and improved On-Time Performance (OTP) by engineering a production-grad

Drove $40M in incremental revenue and improved NPS by engineering a Geospatial Network Allocation model that identified optimal locations for site expansion. Outperformed legacy campaigns by 14% by engineering an Uplift Modeling strategy (Causal Inference) that targeted customers with the highest incremental probability of conversion, and reduced churn by 5% by building a Geospatial Risk Engine th

Achieved a 30% reduction in waste collection route distance by combining XGBoost-based ETA prediction.

Developed Intuitive Manufacturing Dashboards in SQL to integrate IoT data (machines, sensors, and labor).

Master of Science in Optimization and Applied Computer Science.