Data Science
Airbnb Oslo Analytics
Data Scientist
Combined Random Forest regression, spatial features, and Tableau-ready datasets that empowered hosts to reposition pricing relative to neighbourhood signals.
Challenge
Hosts lacked clarity on how neighbourhood dynamics affected pricing decisions in Oslo's fast-moving rental market.
Approach
Blended Random Forest regression, geospatial features, and narrative dashboards to surface pricing leverage points.
Outcome
Pinpointed underpriced districts and equipped hosts with actionable insights for revenue lift.
Highlights
- Pinpointed underpriced districts
- Blended textual and spatial features
- Shared narrative dashboards with stakeholders