Senior / Principal Data Scientist

About HotelTrader

HotelTrader is a New York-based, VC-backed hotel distribution company building the next generation of hotel revenue and distribution technology.

Its platform, The Exchange, connects hotels directly with 160+ travel buyers, providing real-time rates and availability directly from hotel Property Management Systems (PMS) and Central Reservation Systems (CRS), with transparent net-rate distribution.

Shortlisted for the 2026 Skift IDEA Awards, HotelTrader is building an AI-native platform to help hotels optimize pricing, forecast demand, and manage inventory more intelligently.

Role Overview

We are looking for a hands-on Senior / Principal Data Scientist with solid expertise in time-series forecasting, hotel demand prediction, revenue management, and dynamic pricing.

You will build and deploy production-grade machine learning models that help hotels make better pricing, occupancy, and inventory decisions.

Key Responsibilities

- Develop and deploy hotel demand and occupancy forecasting models using booking pace, pickup trends, cancellations, and historical booking curves.
- Build hotel pricing, revenue optimization, and yield management models that drive measurable business impact.
- Develop probabilistic forecasting models using Gradient Boosting, Deep Learning, TFT, DeepAR, and time-series foundation models.




- Work on cold-start forecasting for new hotels with limited or no historical booking data.
- Design dynamic pricing solutions using Reinforcement Learning, Contextual Bandits, and Causal Uplift Modeling.
- Build LLM-powered agents that convert forecasts and business insights into actionable pricing and inventory decisions.
- Work with large-scale datasets using Python, SQL, and Spark.
- Take end-to-end ownership of model development, deployment, monitoring, and continuous optimization.
- Collaborate with product and engineering teams to translate business problems into scalable AI solutions.

Mandatory Skills
- 8+ years of experience in Data Science / Machine Learning.
- Strong hands-on expertise in Python, SQL, and Spark.
- Proven experience building and deploying demand forecasting or occupancy prediction models.
- Experience in hotel revenue management, hotel pricing, yield optimization, or travel/hospitality analytics.
- Strong understanding of time-series forecasting and predictive modeling.
- Demonstrated business impact through production ML models.

Good to Have
- Experience with room allotment, inventory optimization, or buy-and-hold inventory models.
- Experience with Reinforcement Learning and Contextual Bandits.
- Exposure to Temporal Fusion Transformers (TFT), DeepAR, Chronos-2, or TimesFM.
- Experience with LLM agents and AI-driven automation.

📌 Principal Data Scientist (India)
🏢 Recro
📍 India