JOB SUMMARY

The Director of Revenue Management Data Science leads the strategy, development, and optimization of advanced predictive analytics and machine learning capabilities that support Norwegian Cruise Line's revenue management objectives. This role is responsible for transforming complex guest behavior, booking, pricing, and market data into actionable insights that drive ticket revenue, onboard revenue, and yield optimization. The position oversees the development of scalable forecasting models, pricing algorithms, and inventory optimization frameworks while ensuring alignment between technical innovation and commercial strategy. As a key leader, the Director partners across Revenue Management, Pricing, Marketing, Digital Commerce, Finance, IT, and Business Intelligence to enhance decision-making and maximize business performance.

POSITION RESPONSIBILITIES

• Algorithmic Strategy & Modeling Leadership: Own the end-to-end vision, prototyping, production, and continuous auditing of advanced statistical models (including time-series forecasting, price elasticity modeling, mixed-integer programming, and machine learning algorithms) to maximize net ticket yields and passenger cruise days.
• RMS Evolution & Calibration: Partner with IT, Business Intelligence, and Technical Operations teams to elevate Revenue Management System (RMS) logic, user experience, and baseline calibration thresholds. Drive advanced automation and process standardization to improve prediction accuracy and minimize operational workflow cycle times.
• Predictive Demand & Inventory Forecasting: Build, scale, and maintain robust, reusable ticket and onboard revenue forecast models that seamlessly simulate booking curves, cancellation patterns, upgrade behaviors (e.g., Plusgrade), and optimal deployment strategies.
• Commercial Experimentation & Validation: Establish rigorous statistical measurement frameworks, including A/B testing validation, panel data techniques, and revenue attribution models, to quantitatively evaluate the business performance of tactical promotions, digital checkout flows, and dynamic pricing strategies.
• Cross-Functional Executive Influence: Serve as the chief translator of complex technical and algorithmic methodologies into actionable commercial strategies. Communicate data-driven insights, model impacts, and predictive P&L risks to senior leadership and key brand stakeholders across Pricing, Sales, Marketing, Digital Commerce, and Finance.
• Team Development & Culture: Recruit, lead, and mentor a high-performance team of data scientists and analytical managers. Foster an organizational culture of technical innovation, continuous learning, absolute accountability, and operational excellence.

QUALIFICATIONS

DEGREE TYPE:

Bachelor's Degree

FIELD(S) OF STUDY:

Business Administration, Hospitality Management, Finance, Marketing, or a related field

EXPERIENCE

• Bachelor's degree in Data Science, Statistics, Mathematics, Operations Research, Computer Science, Economics, or a related quantitative discipline required.
• Master's degree or Ph.D. in a quantitative field preferred.
• 7–10 years of progressive experience in data science, predictive modeling, advanced analytics, or quantitative business strategy roles.
• 3–5 years of leadership experience managing and developing teams of data scientists, analysts, or technical professionals.
• Experience developing and deploying predictive models that drive measurable revenue and business outcomes.
• Experience within dynamic pricing, revenue management, travel, hospitality, airline, cruise, gaming, or other capacity-constrained industries preferred.
• Experience working with cloud-based data platforms, enterprise analytics tools, and large-scale data environments.

COMPETENCIES & SKILLS

• Advanced Coding Mastery: Expertise in programming languages required for statistical computing and data architecture, specifically Python and advanced SQL.
• Cloud Infrastructure: Deep structural knowledge of cloud-based data warehouses and analytics environments, notably Snowflake, Databricks, or cloud equivalents.
• Data Visualization & Analytics: Strong proficiency architectural engineering within business intelligence tools (specifically Power BI or Tableau) to deliver compelling executive-level data storytelling.
• Revenue Systems: Familiarity with enterprise-grade Revenue Management Systems (e.g., PROS, Sabre, IDeaS) and a strong conceptual grasp of their underlying calibration mechanics and data pipelines.
• Commercial & Financial Acumen: Deep understanding of business P&L management, net corporate yield optimization, and building robust, data-backed business cases for structural modeling and technology investments.
• Strategic Agility: Proven comfort navigating ambiguous commercial challenges, prioritizing high-impact modeling pipelines, and balancing immediate tactical enterprise needs with long-term data infrastructure stability.
• Communication Excellence: Exceptional verbal, written, and narrative presentation skills, with a demonstrated ability to establish cross-departmental alignment and clearly explain complex data concepts to non-technical stakeholders.

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.