The opportunity
Airbnb was born in 2007 when two hosts welcomed three guests to their San Francisco home, and has since grown to over 5 million hosts who have welcomed over 2 billion guest arrivals in almost every country across the globe. Every day, hosts offer unique stays and experiences…
What you'll do
Own short-term, mid-term, and long-term demand forecasting across all Global: Operations teams and channels (phone, messaging, email, back-office etc.).
Design, develop, and maintain statistically robust demand forecasting models: using time series and machine learning techniques (e.g., exponential smoothing, ARIMA, regression-based models etc.).
Perform trend, seasonality, and variance decomposition; detect structural: breaks, outliers, and demand anomalies.
Quantify forecast uncertainty through confidence intervals, error distributions, and bias analysis.
Perform scenario modeling for peak demand periods, product launches, growth: initiatives, and unplanned demand events.
Continuously assess model performance using statistical accuracy metrics (MAPE, RMSE, MAE, bias etc).
What they're looking for
- Establish model governance standards, including documentation, validation,: back-testing, and post-mortem analysis.
- Research, prototype, and implement new forecasting and optimization techniques as business needs evolve.
- Perform scenario planning and sensitivity analysis to quantify trade-offs: between service levels, cost, and utilization.
- In partnership with the Analytics and Data Engineering team, design and build: scalable planning data pipelines, dashboards, and automate forecasting and capacity models to improve scalability, repeatability, and timeliness.
