Background
As Senior Data Scientist II at Teradata, I worked on one of the most ambitious forecasting projects in Nordic retail. IKEA needed accurate sales forecasts across their global operation — from Sweden to Japan.
My approach
I built a forecasting pipeline that combined time series algorithms with local market understanding. The system accounted for everything from national holidays to local weather conditions.
Technologies
- Python & R for statistical modeling
- Spark for distributed data processing
- Teradata for data warehousing
Results
The project improved IKEA’s ability to predict sales and optimize their supply chain.
