Director, Revenue Management Data Science

Posted 3 Days Ago
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Miami, FL, USA
In-Office
Senior level
Transportation • Travel • Hospitality
The Role
Lead strategy and delivery of predictive analytics and ML for revenue management. Build and deploy forecasting, pricing, and inventory optimization models; drive RMS calibration, A/B testing, and revenue attribution; translate technical output for executives; partner cross-functionally; recruit and mentor a data science team to maximize ticket and onboard revenue.
Summary Generated by Built In

GROW YOUR CAREER WITH US
At Norwegian Cruise Line Holdings (NCLH), we know our future success depends on our ability to attract and retain the very best talent. Our brands deliver vacations of a lifetime with innovative product offerings, a high level of service and unique guest experiences aboard each vessel and we’re continually seeking applicants who are passionate about hospitality and committed to being their personal best. As you learn more about our company, we think you will agree that there is no better time than now to become a member of the NCLH family!
APPLY ONLINE
If you’re interested to be considered for this position, please click the blue APPLY button at the top of the page to get started. All candidates must complete an on-line application to be considered.

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.

ABOUT NCLH
Norwegian Cruise Line Holdings Ltd. (NYSE: NCLH) is a leading global cruise company which operates the Norwegian Cruise Line®, Oceania Cruises® and Regent Seven Seas Cruises® brands. The combined brands currently operate 32 ships, employ over 35,000 shipboard crew from more than 110 different countries and visit approximately 700 different port destination each year.
LEARN MORE ABOUT OUR COMPANY:
At a Glance                                      
Brand Overview                    
Norwegian Cruise Line     
Oceania Cruises
Regent Seven Seas Cruises

New Releases                       
EQUAL OPPORTUNITY EMPLOYER
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.

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.

Skills Required

  • Bachelor's degree in Data Science, Statistics, Mathematics, Operations Research, Computer Science, Economics, or related quantitative discipline
  • 7-10 years progressive experience in data science, predictive modeling, advanced analytics, or quantitative business strategy
  • 3-5 years leadership experience managing and developing teams of data scientists or technical professionals
  • Experience developing and deploying predictive models that drive measurable revenue and business outcomes
  • Experience working with cloud-based data platforms, enterprise analytics tools, and large-scale data environments
  • Expertise in Python and advanced SQL
  • Deep knowledge of cloud data warehouses/analytics environments (Snowflake, Databricks, or equivalents)
  • Strong proficiency with business intelligence tools (Power BI or Tableau)
  • Commercial and financial acumen in P&L management and yield optimization
  • Exceptional verbal, written, and presentation skills for executive communication
  • Master's degree or Ph.D. in a quantitative field
  • Experience within dynamic pricing, revenue management, travel, hospitality, airline, cruise, gaming, or capacity-constrained industries
  • Familiarity with enterprise Revenue Management Systems (e.g., PROS, Sabre, IDeaS)
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The Company
44,500 Employees
Year Founded: 1966

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