Data Scientist, Revenue Management Systems

Job Summary

The Data Scientist within Revenue Management Systems will be responsible for building, scaling, and validating predictive models, forecasting logic, and advanced analytics frameworks that power Norwegian Cruise Line's dynamic pricing and inventory management decisions. The role bridges statistical engineering with commercial operations—translating massive datasets, historical transaction curves, and high‑intent guest behavioral data into clear, high‑yield revenue recommendations.

• Design, write, and maintain scalable algorithms and machine learning models for booking curves, price elasticity, cancellation rates, and passenger cabin upgrades.
• Query, clean, aggregate, and manipulate large‑scale datasets from disparate corporate ecosystems using Snowflake, SQL, and Python to ensure reliable inputs for quantitative modeling.
• Monitor, fine‑tune, and analyze baseline calibration thresholds within enterprise Revenue Management Systems to reduce forecast variances and automate routine algorithmic workflows.
• Formulate rigorous tracking and measurement frameworks, using statistical methodologies and panel data techniques to validate revenue impacts of tactical promotions and digital pricing optimizations.
• Architect, deploy, and maintain insightful data visualization dashboards in Power BI or Tableau to translate modeling results and performance metrics into clear stories for commercial stakeholders.
• Partner closely with IT and data engineering teams to operationalize prototypes into robust production systems, while communicating quantitative logic clearly to non‑technical business partners.

• Bachelor’s Degree in Business Administration, Hospitality Management, Finance, Marketing, or a related field.
• 2–5 years of progressive professional experience as a data scientist, quantitative analyst, or modeler—ideally building systems that influence business pricing, sales, or financial forecasting.
• Hands‑on experience manipulating, structuring, and scrubbing large raw datasets within enterprise cloud‑based or local architectures.
• Prior experience working in dynamic commercial fields with highly perishable inventory (e.g., cruise lines, aviation, hospitality, logistics, or consumer tech) is highly preferred.

• Strong mastery of programming languages required for statistical computing, data architecture, and ETL execution—specifically Python and advanced SQL.
• Hands‑on familiarity extracting and joining complex relational data within cloud data platforms like Snowflake, Databricks, or equivalent.
• Demonstrated capability building, hosting, and automating reports or data visualization dashboards in Power BI or Tableau.
• Knowledge of regression analysis, time‑series forecasting (ARIMA/Prophet), optimization algorithms, and common machine learning packages (scikit‑learn, XGBoost, etc.).
• Excellent analytic curiosity and ability to translate findings into logical business mechanics.
• Strong time‑management skills and the ability to take an abstract business request from exploratory data analysis to model testing and dashboard delivery.
• Collaborative communicator who can speak comfortably with both database administrators and non‑technical business leaders.

It is Norwegian Cruise Line Holding’s policy not to discriminate against any employee or applicant for employment because of race, color, religion, sex, national origin, age, disability, or marital or veteran status. The above statements are intended to describe the general nature and level of work being performed by people assigned to this classification. They are not to be construed as an exhaustive list of all responsibilities, duties, and skills required of personnel so classified.

All personnel may be required to perform duties outside of their normal responsibilities from time to time, as needed.