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About the Role
The Data Scientist within Revenue Management Systems will build, scale, and validate predictive models, forecasting logic, and advanced analytics frameworks to support dynamic pricing and inventory management decisions. This role translates complex data into revenue recommendations, working closely with leadership, data engineers, and revenue managers.
Responsibilities
- 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 using Snowflake, SQL, and Python for quantitative modeling.
- Monitor, fine-tune, and analyze baseline calibration thresholds within Revenue Management Systems to reduce forecast variances and automate workflows.
- Formulate tracking and measurement frameworks using statistical methodologies to validate the revenue impacts of promotions and pricing optimizations.
- Architect, deploy, and maintain data visualization dashboards in Power BI or Tableau for commercial stakeholders.
- Partner with IT and data engineering teams to operationalize prototypes and communicate quantitative logic to non-technical partners.
Requirements
- Bachelor's degree in Data Science, Statistics, Mathematics, Operations Research, Economics, Computer Science, or a heavily quantitative discipline.
- Master's degree (MS) in a quantitative field is a plus with equivalent professional experience.
- 3–5 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 in dynamic commercial fields with highly perishable inventory (e.g., cruise lines, aviation, hospitality, logistics, or consumer tech) is highly preferred.
- Experience presenting complex outputs clearly and concisely to influence leadership.
Skills
- Python
- Advanced SQL
- Snowflake
- Databricks
- Power BI
- Tableau
- Regression analysis
- Time-series forecasting (ARIMA/Prophet)
- Optimization algorithms
- Machine learning packages (scikit-learn, XGBoost)
- Analytical curiosity
- Execution and delivery
- Collaborative communication
Experience Level
- 3-5 years
Education Level
- Bachelor's Degree
About the Company
- Norwegian Cruise Line Holdings Ltd. (NYSE: NCLH) is a leading global cruise company operating the Norwegian Cruise Line®, Oceania Cruises® and Regent Seven Seas Cruises® brands.
- The combined brands operate 32 ships, employ over 35,000 shipboard crew from more than 110 different countries and visit approximately 700 different port destinations each year.
Equal Opportunity
- 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, and marital or veteran status.