The AVP, Revenue Management Systems & Operations Research is responsible for formulating and executing strategies for decision support tools used by revenue management and deployment in support of all brands, overseeing all systems, models and reporting for revenue. The AVP will maintain and enhance the suite of revenue management tools that forecast, maximize, and report on revenue streams in the billions, including critical corporate revenue and customer deposit reporting.
The AVP will spearhead the evolution of our systems and tools to enable the revenue planning team to evolve to provide a deeper level of insight, incorporating new sources of data and insights, including macro, consumer, competitive, and onboard revenue data. This includes the development of new tools and reporting that can evolve our reporting to improve capabilities to provide a greater level of insight to drive predictability and profitability.
The AVP will oversee the complete redesign and update of all revenue and deployment reporting resulting from the new Reservations and ERP systems. This includes new revenue and customer deposit reporting, updates to all revenue management reports, and the full implementation of Silversea. They will also partner with the Data team to ensure the future organizational structure best supports all data, analytical, and reporting needs.
RESPONSIBILITIES
Oversee Four Teams
RM Development and Systems: This is a team of data engineers responsible for managing the systems that feed all the data into the reporting and models. This includes both ensuring that the data is piped in correctly, maintaining automation and controls to ensure data integrity and quality. This team also partners cross-functionally with the Corporate Data team which manages data standards and governance for the Group. RM Operations Research & Predictive Analytics: This team drives predictive modeling to generate long-term revenue plans and highlight the impact of internal and external factors on the business. This includes ongoing maintenance of predictive models that enable revenue maximization. This is a team of SMEs related for models to support revenue management, and this team partners cross-functionally with the Group’s Data Analytics & AI team. Data Visualization and BI: Automation and visualization are key to efficient analytics across the organization. This team will drive increased reporting automation and dashboarding for the revenue, deployment, and finance teams. Additionally, they will consult with internal clients to understand business needs and adapt strategies accordingly. Deployment Systems and Optimization: This team leads the design, development, and management of all deployment tools and systems, ensuring all decarbonization-related considerations (CII, EEXI, EU Tax) are incorporated into deployment decisions and the strategic plan. The team works with external vendors and corporate deployment teams for all three brands in implementing an itinerary planning system, as well as a database with competitive insights.Drive Data Science and Analytics
Provide Leadership for Operations Research team: Oversee the application of operations research and advanced quantitative methodologies to develop models that maximize revenue, including forecasting, statistics, econometric modeling, linear programming, and other optimization algorithms. Deploy data science and machine learning to drive profitability, predictably: Build and maintain models that inform revenue optimization strategies, deployment optimization, and to improve forecast capabilities. Enhance models and decision-making tools by integrating new sources of insight, such as marketing and macro data. Continuous Improvement: Remain at the forefront of operations research and machine learning techniques to ensure continuous improvement of all models.Innovate and Lead for the Future
Adapt to Change: Anticipate business changes and guide the department in adapting processes and decision-making tools to meet future business needs. Align with Leadership: Consult with key members of brand leadership to ensure alignment, incorporate brand strategy, and provide insights and analytics to influence decisions. Drive Strategic Implementation: Set and implement strategies for automation, visualization, and revenue analytics, partnering with the brands. Lead Development of New Tools and Capabilities: Lead the development of new reporting and forecasting tools to support PCP and Onboard Revenue areas, creating a corporate capability and a single source of truth for this data in partnership with brand onboard revenue teams and the digital/e-commerce teams.Develop and Strengthen Teams
Encourage Collaboration and Innovation: Promote a collaborative environment where team members can share ideas, work together, and innovate. Encourage cross-functional teamwork to leverage diverse skill sets. Foster Continuous Learning: Encourage and provide opportunities for team members to continuously develop their technical skills and knowledge through training, certifications, workshops, and conferences. Provide Constructive Feedback and Recognition: Regularly provide constructive feedback to help team members grow and improve. Recognize and reward their achievements to motivate and retain top talent. Support and Mentor Talent: Act as a supportive leader and mentor, offering guidance and support to help team members navigate challenges and advance in their careers.Collaborate, Consult, and Communicate Effectively
Support Corporate Initiatives: Support various company initiatives with analytical and modeling expertise, providing relevant and actionable RM-related information in the most effective format and medium. Consult across all levels: Provide consulting expertise at all levels, including department executives, to understand underlying business needs, changing patterns, and market conditions, developing practical solutions to drive revenue and reduce costs. Present clearly: Clearly explain tools and results to management, developing and delivering clear, concise presentations that communicate technical methods and impacts in business terms.
QUALIFICATIONS
Education and experience that will enable you to excel: You have a Master’s degree in Operations Research, Industrial Engineering, Econometrics or Statistics, with an MBA preferred. You bring at least 10 years of work experience in a related field such as marketing modeling/data science. You have experience with retention models, propensity models, and optimization models.
The ability to translate business needs into mathematical models and model results into business meanings: You possess advanced analytical skills, particularly in mathematical modeling, and are proficient in technical and mathematical programming languages and BI tools, including PL/SQL, SAS, PowerBI, CPLEX, VB, .NET, and Databricks. You can define problems, trace their causes, and apply quick reality checks while reviewing results. You can translate large amounts of data into meaningful business conclusions and develop creative solutions. You have proven experience with systems management.
Strong leadership skills: You inspire and motivate your team to achieve their best, communicate a clear vision, and foster a positive and productive work environment. You are empathetic, adaptable, and capable of making decisive, well-informed decisions while maintaining integrity and accountability.
The capacity to communicate clearly and effectively to both business and technical audiences: You excel at bridging the gap between business and technical teams, ensuring clear and effective communication across all levels. Your skills enable you to convey complex technical concepts in a way that is easily understood by non-technical stakeholders, and you can articulate business needs and strategies to technical teams, fostering mutual understanding and collaboration.