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Royal Caribbean Cruises Ltd

Manager, Data Science

Miami, FL, United States

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Job details

Posting language: English
Posted: Nov 9, 2026

Original job description

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’s AI and Analytics Team has an exciting career opportunity for a full time Manager, Data Science reporting to the Sr. 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 extending AI-driven commercial decisioning across Onboard Revenue and Casino at Royal Caribbean Group. The role connects pricing, targeted offers, personalization, product recommendations, guest value, and casino offer decisioning into measurable production outcomes. It requires statistical, machine learning, optimization, and experimentation depth, combined with practical commercial judgment and the ability to translate complex guest and product signals into decisions around price, offer, product, guest, and timing.

People Leadership: Lead, coach, and develop data science talent across Onboard Revenue and Casino, moving technical coaching, business translation, and day-to-day execution closer to the team while reinforcing end-to-end ownership of commercial value.
Delivery Accountability: Own reliable delivery of pricing, targeted-offer, personalization, recommendation, and casino decisioning roadmaps from problem framing through production adoption, controlled measurement, and ongoing operations.
Technical Oversight: Provide technical direction across price-response modeling, demand forecasting, propensity and uplift modeling, recommender systems, segmentation, constrained optimization, experimentation, and real-time decisioning.
Portfolio Management: Prioritize work across PCP pricing, promotions, Targeted Offers, MyCruise personalization, shipboard offers, and Casino based on incremental revenue potential, adoption readiness, dilution risk, data readiness, and production feasibility.
Stakeholder Management: Partner with Onboard Revenue, Casino, Digital, E-Commerce, Marketing, Product, AI Engineering, Data Engineering, and brand leaders to define decision owners, business guardrails, measurement plans, and operating workflows.
Change Management: Embed recommendations into analyst, merchandising, campaign, shipboard, and casino operating processes; build trust through transparent logic, workflow integration, training, and control-group measurement.
Governance & Risk: Ensure guest-level targeting, offer, pricing, and reward decisions meet Responsible AI, privacy, fairness, explainability, legal, validation, and model-risk expectations, with explicit controls against promotional dilution and conflicting guest contacts.
Resource Planning: Forecast capacity across model development, experimentation, production support, campaign execution, pricing coverage, and stakeholder adoption so the roadmap scales without creating a senior-leader or operational bottleneck.
Talent Strategy: Build depth across pricing science, causal measurement, propensity and uplift modeling, recommendations, optimization, and production decision systems while developing strong business-facing 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.

HOW HAS THE JOB CHANGED/GROWN

The role has expanded from managing individual models and analyses to leading an integrated commercial decisioning portfolio spanning pricing, targeted offers, personalization, recommendations, and Casino. The manager provides the technical and delivery leadership needed to accelerate execution while enabling senior leaders to focus more deeply on the highest-value strategic decisions.

INTERNAL/ EXTERNAL RELATIONSHIPS

Internal – Onboard Revenue, Casino, Digital, E-Commerce, Marketing, Product, AI Engineering, and Data Engineering: Translate commercial opportunities into analytical roadmaps and embed model outputs into pricing, merchandising, campaign, digital, and shipboard workflows.
Internal – Brand and Finance stakeholders: Align business guardrails, test/control measurement, value tracking, and adoption accountability for revenue-generating decisions.
External – Data, model, optimization, and consulting partners: Evaluate external capabilities based on incremental value, accuracy, integration effort, responsible use, risk, and long-term RCG leverage.

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 Group and each of its subsidiaries prohibit and will not tolerate discrimination or harassment.

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More about this job

Skills

Machine learning
Leadership
Coaching
Translation
Forecasting
Paramedic
Stakeholder management
Data engineering
Change management
Merchandising
Workflow
ML
Statistics
Financial capability
Communication skills
Vendor management

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