Selected machine learning work from my time at VF Corporation and Kohl's.

VF Corporation Senior Data Scientist · 2025 - Present

Vans Inventory Rebalance

Leading the Inventory Rebalance initiative for the Vans AMER region: optimizing how inventory is allocated across the distribution network so that stock sits where demand actually is, rather than piling up in some locations while others run short. Built on Python, Databricks, and machine learning.

In progress: reducing stock imbalances across the AMER distribution network.

PythonDatabricksOptimizationMachine Learning

VF Corporation Senior Data Scientist · 2025 - Present

Automated Demand Forecasting & Inventory Optimization Pipeline

Rebuilt the Vans demand forecasting and inventory optimization workflow as a single automated, end-to-end pipeline running on Python, AWS, and Databricks, replacing a slow manual process.

Cut model runtime by more than 90%, from 48 hours down to 4.

PythonAWSDatabricksForecasting

Kohl's Data Scientist I, Product Recommendations · 2023 - 2025

Kohls.com Product Recommendation Engine

Designed, built, and deployed a Hybrid Matrix Factorization recommendation model for Kohls.com product detail pages using LightFM, BigQuery, Vertex AI, and Kubeflow. Led the architecture and code reviews and drove the cross-functional rollout with engineering and product.

$13.8M revenue lift, with personalization coverage expanded from 500K to 20M customers.

LightFMBigQueryVertex AIKubeflowPython

Kohl's Supply Chain Movement · 2021 - 2023

U.S. Port Inventory Arrival Forecasting

Prototyped, evaluated, and then productionized a LightGBM model that forecasts when inventory will arrive at U.S. ports. Refactored notebooks into modular Python and Kubeflow components and built a Streamlit dashboard for real-time model monitoring.

Improved 6-month forecast accuracy by 67%.

LightGBMPythonKubeflowOptunaStreamlit