Enterprise Retail & supply chain
Electronic Fulfillment Center Forecasting
Architect & Lead Data Scientist · H-E-B
A 21-day, hourly forecast of orders and units for every fulfillment-center and store pair, feeding staffing and capacity planning.
- WMAPE in staging
- ~14%
- EFCs × stores
- 9 × 73
- 21-day horizon
- Hourly
The problem
Fulfillment centers need to know, hour by hour and weeks ahead, how many orders and units each store pairing will generate in order to staff and plan capacity.
What I built and led
- Architected a 21-day multi-horizon forecast of hourly orders and units for every EFC–store pair (9 EFCs, 73 stores), ensembling an ARIMA baseline, global LightGBM models and a Temporal Fusion Transformer.
- Engineered the MLOps pipeline on Databricks (AWS): MLflow-tracked experimentation and model selection, weekly retraining and daily inference via model serving.
- Feeds EFC staffing and capacity planning, with staff allocation partly live.
Results
- ~14% WMAPE in staging
- 9 × 73 EFCs × stores
- Hourly 21-day horizon