Last update: 2023. All opinions are my own.

1. Overview

Collaborated with a team to predict raw material demand and improve inventory turnover for Industrias Duero.

2. Data Pipeline

We integrated supply-chain data sources and built a clean forecasting dataset, then validated assumptions with stakeholders.

3. Modeling

  • Implemented time-series and ML forecasting strategies.
  • Compared classical models with ML baselines.
  • Designed evaluation to reflect operational lead times.

4. Outcomes

  • Analyzed over 1.5 million data points across the supply chain.
  • Built dashboards to communicate forecasting outcomes.
  • Delivered recommendations for inventory turnover improvements.

5. Skills and Tools

  • Python
  • Facebook Prophet
  • Time-series forecasting
  • XGBoost, CatBoost
  • Microsoft Power BI