Data Scientist
Senior Data Scientist specializing in supply chain optimization, demand forecasting, and logistics analytics. 7+ years turning complex data into operational impact at Nike and leading logistics companies.
Featured Projects
Supply Chain Container Flow Optimization
Analyze detailed shipment and order data to map container movements from origin to destination, identifying optimization opportunities that reduce lead times and costs. Track KPIs including on-time performance, volume, and carton distribution at container and PO-item levels.
Demand-Driven Allocation Algorithms
Integrated real-time and historical demand signals into allocation algorithms to improve forecast accuracy and responsiveness. Built end-to-end data pipelines, developed optimization models, and automated the entire allocation process from data ingestion to output delivery.
Expected Delivery Date & Inventory Flow Modeling
Leveraged demand signals to recommend inventory padding and flow through distribution centers. Built stock/flow simulations accounting for replenishment cycles, safety stock, and lead times. Translated DC operational rules into model logic for accurate delivery date promises.
NLP-Enhanced Customer Search System
Enhanced internal search capabilities for customer call centers by applying NLP methods and integrating with the ElasticSearch API.
Less-Than-Truckload Forecasting
Improved forecast accuracy (MAPE) for daily tonnage predictions, supporting more effective labor planning and resource allocation.