Description I'm a PhD-level Lead Data Scientist with 4+ years of industry experience building production forecasting and predictive modeling systems at global scale. At Hilton Hotels Corporation, I architect forecasting pipelines serving 8,000+ hotels across 120+ countries — powering revenue optimization, pricing, and financial planning.
What I offer:
- Demand, revenue, and time series forecasting (ARIMA, Prophet, ETS, N-BEATS, LSTMs, Transformers)
- Hierarchical forecasting with reconciliation across multiple levels
- Probabilistic forecasting with confidence intervals and risk quantification
- ML predictive models using XGBoost, LightGBM, Random Forest, and ensemble methods
- Cold-start solutions for entities with limited or no historical data
- End-to-end pipelines: data ingestion, model training, validation, and deployment
- Automated backtesting frameworks with MAPE, RMSE, and coverage metrics
Industries I've worked in: Hospitality, Transportation, Manufacturing, Energy
Tools: Python, SQL, AWS, Airflow, Docker, Tableau, Power BIHospitality, Transportation, Manufacturing, Energy
