Manager, Data Science

Royal Caribbean Cruises Ltd; Miami (FL); On-site; USD 140,000 - 210,000; Full time

Job summary

Royal Caribbean Group seeks a Manager, Data Science to lead a team responsible for building the intelligence layer enabling Marketing to identify valuable customers, target Persuadable audiences, and design effective experiences. The role spans CLV, targeting, loyalty, synthetic-personality testing, and media measurement.

You will lead cross-functional teams, deliver production-grade models, and ensure governance and Responsible AI standards across campaigns and analytics initiatives from design

Qualifications

• Experience delivering ML/optimization/experimentation or GenAI solutions in production.
• Strong statistical and modeling foundations are required.
• Ability to translate business strategy into sequenced analytical roadmaps and value tracking.

Responsibilities

• Lead, coach, and develop data science talent across Marketing, CLV, Loyalty, and experimentation.
• Own delivery of CLV assets, propensity and audience models, and media measurement from design to activation.
• Provide technical direction across models, segmentation, recommender systems, causal inference, and model monitoring.
• Prioritize Marketing work by value, activation readiness, data consent, and model risk.
• Partner with Marketing, E-Commerce, Loyalty, Digital, and other teams to translate growth questions into analytics roadmaps.

Skills

ML

Optimization

Experimentation

GenAI

Leadership

Job description

Select how often (in days) to receive an alert:

Manager, Data Science

Journey with us! Combine your career goals and sense of adventure by joining our exciting team of employees. Royal Caribbean Group is pleased to offer a competitive compensation and benefits package, and excellent career development opportunities, each offering unique ways to explore the world.

We are proud to be the vacation-industry leader with global brands — including Royal Caribbean International, Celebrity Cruises and Silversea Cruises — the most innovative fleet and private destinations, and the best people. Together, we are dedicated to turning the vacation of a lifetime into a lifetime of vacations for our guests.

The Royal Caribbean Group’sDigital Teamhas an exciting career opportunity for a full timeManager, Data Science reporting to theSr. Manager, Data Science.

The position is onsite and based in Miami, Florida.

The position is also not eligible for work authorization sponsorship.

Position Summary:

To lead a data science team accountable for building the intelligence layer that helps Marketing determine which customers matter, who is persuadable, what experience or message to present, and whether interventions create incremental value. The portfolio spans customer lifetime value (CLV), customer targeting, loyalty, synthetic-personality testing, and media measurement. The role requires strong predictive modeling, causal measurement, experimentation, segmentation, and GenAI experience, together with the ability to turn analytical outputs into activated audiences, measurable campaigns, and durable customer intelligence.

• People Leadership: Lead, coach, and develop data science talent across Marketing, customer targeting, CLV, Loyalty, and experimentation, placing technical coaching and business translation close to the delivery teams.

• Delivery Accountability: Own delivery of CLV assets, propensity and audience models, Loyalty simulation, synthetic-personality testing, and media measurement from analytical design through activation, adoption, and measured outcomes.

• Technical Oversight: Provide technical direction across CLV, propensity and uplift modeling, segmentation, recommender systems, causal inference, brand-lift testing, simulation, synthetic-customer evaluation, and model monitoring.

• Portfolio Management: Prioritize Marketing work by decision value, activation readiness, data and consent readiness, measurement feasibility, model risk, and reuse across Royal Caribbean International, Celebrity Cruises, and Silversea.

• Stakeholder Management: Partner with Marketing, E-Commerce, Loyalty, Digital, Consumer Insights, Media Network, Product, AI Engineering, Data Engineering, and brand teams to translate growth questions into analytical roadmaps and activation plans.

• Change Management: Drive adoption through audience activation, campaign operating routines, Loyalty scenario planning, test-and-learn standards, stakeholder training, and clear accountability for using model outputs.

• Governance & Risk: Ensure customer models and synthetic testing follow Responsible AI, privacy, consent, explainability, validation, auditability, and ethical-use expectations, including controls for protected data and marketing eligibility.

• Resource Planning: Forecast capacity across model refreshes, campaign scoring, experiment design, CLV data production, Loyalty simulations, media studies, and production support to avoid fragmented one-off delivery.

• Talent Strategy: Build depth across customer analytics, causal measurement, experimentation, segmentation, CLV, recommendations, and GenAI-based research while developing strong partners to Marketing and Digital leaders.

Qualifications:

• Experience: Demonstrated experience appropriate to manager scope delivering ML, optimization, experimentation, or GenAI solutions that moved beyond analysis into production use or business decisioning. Relevant experience in the assigned portfolio domain is strongly preferred.

• Technical Credibility: Strong grounding in statistics, machine learning, optimization, GenAI methods, evaluation, and production model lifecycle practices, with the judgment to challenge assumptions and explain tradeoffs.

• Strategic Leadership: Ability to translate business strategy into sequenced analytical roadmaps, model portfolios, adoption plans, and value tracking routines aligned to data scientists, product owners, AI engineering, data engineering, and business stakeholders.

• Financial Acumen: Working knowledge of value sizing, ROI framing, experimentation economics, cloud/model operating costs, and investment tradeoffs.

• Communication: Clear communication skills with data scientists, product owners, AI engineering, data engineering, and business stakeholders, including the ability to explain model logic, uncertainty, tradeoffs, risks, and recommended decisions in business terms.

• Change Leadership: Track record of driving adoption of analytical products, experimentation practices, model governance, and data-driven operating routines across teams with different analytical maturity levels.

• Governance: Knowledge of Responsible AI, privacy, explainability, validation, auditability, and ethical use of data, with experience embedding governance into data science workflows.

• Vendor Management: Ability to evaluate external data, model providers, optimization tools, GenAI services, and consulting support based on business value, accuracy, integration effort, risk, and long-term leverage.

• Organizational Design: Understanding of how to scale data science teams, intake models, value governance, production support, stakeholder engagement, and career paths as analytical demand grows.

We know there's a lot to consider. As you go through the application process, our recruiters will be glad to provide guidance, and more relevant details to answer any additional questions. Thank you again for your interest in Royal Caribbean Group. We'll hope to see you onboard soon!

It is the policy of the Company to ensure equal employment and promotion opportunity to qualified candidates without discrimination or harassment on the basis of race, color, religion, sex, age, national origin, disability, sexual orientation, sexuality, gender identity or expression, marital status, or any other characteristic protected by law. Royal Caribbean Groupand each of its subsidiaries prohibit and will not tolerate discrimination or harassment.