Senior/Principal Data Scientist - Hotel Revenue Management - Hospitality Technology

About the Opportunity:

• We are hiring an experienced Senior/Principal Data Scientist for a confidential, VC-backed, New York-based hotel distribution and technology company.
• The company is building an AI-native revenue and distribution platform that enables hotels to optimise pricing, distribute inventory and make smarter revenue decisions.
• Its platform connects hotels directly with 160+ travel buyers, providing real-time rates and availability directly from hotel PMS/CRS systems.
• The company has also been shortlisted for the 2026 Skift IDEA Awards.

Role Overview:

We are looking for a hands-on Data Science professional with deep domain expertise in hotel revenue management, demand forecasting, pricing and inventory optimisation.

The ideal candidate should have experience building and deploying forecasting and pricing models in production, with a clear understanding of how these models translate into commercial and revenue impact for hotels.

Key Responsibilities:

• Build and improve probabilistic hotel demand and occupancy forecasting models.
• Develop booking-curve models covering pace, pickup, cancellations and booking patterns.
• Design and optimise dynamic pricing and yield management models.
• Work on reinforcement learning, contextual bandits and causal uplift modelling for pricing decisions.
• Explore deep learning approaches such as TFT, DeepAR and time-series foundation models like Chronos-2 and TimesFM.
• Build solutions for new hotels with limited or no historical booking data.
• Develop AI/LLM-powered agents to translate forecasts into actionable pricing and inventory decisions.
• Drive measurable improvements in hotel revenue, occupancy and inventory utilisation.

Required Skills & Experience:

• 8+ years of experience in Data Science, Machine Learning or Applied Analytics.
• Strong hands-on expertise in Python, SQL and Spark.
• Proven experience in hotel demand and occupancy forecasting in production environments.
• Strong experience building hotel pricing, revenue management or yield optimisation models.
• Ability to demonstrate measurable business impact through deployed models.
• Strong understanding of hotel booking patterns, inventory distribution and revenue optimisation.

Good to Have:

• Experience with room allotment and buy-and-hold inventory models.
• Exposure to reinforcement learning, contextual bandits and causal modelling.
• Experience with LLM agents and AI-driven decision systems.
• Experience working with hotel PMS/CRS data.

Preferred Industry Background:

• Professionals currently or previously associated with:

• 1. OTAs: MakeMyTrip, Goibibo, Cleartrip, Agoda, OYO.
• 2. Hotel RMS Platforms: IDeaS, Duetto, Lighthouse.
• 3. Other Ecosystems: Bed banks, hotel chains and hospitality technology companies.

Engagement Model:

• Initial engagement of 6 months.
• Fractional consulting commitment of approximately 10 - 15 hours per week.
• Some weekend availability may be required.
• Hourly or daily consulting fee, depending on experience and expectations.
• Open to full-time engagement for the right candidate.

Interested?:

• If you have built and deployed hotel forecasting, pricing or revenue optimisation models and are interested in a fractional consulting opportunity, we'd love to connect.
• Please share your updated resume along with:
• 1. Relevant hotel-tech / revenue management experience.
• 2. Availability per week.
• 3. Expected hourly or daily consulting fee.
• 4. Current location and notice period.
• Apply or DM me directly.