Lead Scientist, Forecasting

We are an ambitious, well-funded, high-growth global technology company transforming the hotel industry.  At Duetto, we are passionate about creating innovative analytical solutions to help hoteliers thrive.  Although we work hard, the work atmosphere is casual, flexible, collaborative, and most of all, fun.  

Duetto offers an open and collaborative work environment and believes that by cultivating a team with diverse backgrounds, perspectives, and experiences, it will continue to lead the industry with its cutting-edge platform-based hospitality technology. 

We are seeking a Lead Data Scientist with deep expertise in forecasting and Bayesian modeling to lead the development of scalable, production-ready machine learning models for demand forecasting and other core challenges in hospitality—such as cancellations, overbooking risk, and pricing response.

In this role, you will design and implement the scientific foundation behind Duetto’s forecasting engine, taking on the unique challenge of building and maintaining thousands of personalized models—one for each hotel partner—tailored to their unique market dynamics and booking behavior.

This is an opportunity for a hands-on, full-stack data scientist who thrives in ambiguity, has strong modeling intuition, and is energized by the challenge of building intelligent systems at scale in a complex, real-world domain.

• Lead the design, development, and deployment of forecasting and pricing models using a blend of classical time series, deep learning and Bayesian statistical techniques.
• Develop hierarchical forecasting frameworks, including multi-level Bayesian models, that scale across thousands of hotel properties.
• Build uncertainty quantification frameworks to increase trust and robustness in forecasts.
• Guide model architecture choices—balancing complexity, interpretability, and operational feasibility.
• Collaborate closely with engineering to deploy and monitor models in production (e.g., using AWS SageMaker).
• Translate model outputs into actionable insights in partnership with product and business stakeholders.
• Define and execute model performance measurement strategies, including causal inference and uplift modeling.
• Present findings, experimental results, and strategic recommendations to senior leadership.

• MS or PhD in Statistics, Econometrics, Computer Science, Operations Research, or a related quantitative field.
• 5+ years of experience delivering impactful data science solutions in production environments.
• Expertise in time series forecasting, including classical methods (e.g., ARIMA, Exponential Smoothing, State Space Models) and deep learning (e.g., RNNs, Temporal Fusion Transformers).
• Practical experience with Bayesian modeling, including hierarchical models and probabilistic programming (e.g., PyMC3, Stan).
• Proficiency with ML/DL frameworks (e.g., PyTorch, TensorFlow, scikit-learn, DARTS) and programming languages (Python, R, SQL).
• Familiarity with cloud platforms and MLOps tools (e.g., AWS SageMaker, MLflow) for scalable model development and deployment.
• Strong communication and presentation skills, capable of conveying complex analytical concepts to non-technical stakeholders.
• Prior experience in the hospitality, travel, or revenue management domain is highly desirable.
• Experience designing model evaluation and impact measurement frameworks, including causal inference.

About Duetto: 

Duetto delivers a suite of SaaS cloud-native applications for hospitality businesses to optimize every booking opportunity for greater revenue impact. The unique combination of hospitality experience and technology leadership drives Duetto to look for innovative solutions to industry challenges. The software as a service platform allows hotels, casinos, and resorts to leverage real-time dynamic data sources and actionable insights into pricing and demand across the enterprise. For more information, please visit https://www.duettocloud.com/.