Principal Data Scientist

Responsibilities:

• Probabilistic forecasting: booking-curve and gradient-boosting models through to TFT and DeepAR, plus time-series foundation models (Chronos-2, TimesFM) for new hotels with no history.
• Dynamic pricing: reinforcement learning, contextual bandits, and causal uplift models that move real revenue.
• LLM agents that turn forecasts into live pricing and inventory actions.

Requirements:

• 8+ years in data science, and you still write code (Python, SQL, and Spark).
• Hotel demand/occupancy forecasting (pace, pickup, cancellations) that you've shipped to production.
• Hotel pricing or yield models that drove real decisions, with measurable $ impact.
• Bonus: room allotment / buy-and-hold inventory experience.

Skills

Data Science, Hotel, Python