Data Scientist - Transformation Hub

Overview

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.

Royal Caribbean Group is seeking an experienced and inquisitive Data Scientist – Transformation Hub to join our Finance Data & Insights team with a dedicated focus on supporting the CFO organization.

The position is onsite and based in Miami, Florida. The position is also not eligible for work authorization sponsorship.

Position Summary

In this role, you will use advanced analytics, machine learning, and optimization to ensure the right products, parts, and provisions are in the right place, at the right time, and at the right cost—directly impacting our guests, crew, and operations worldwide.

You Will

• Build and deploy predictive and optimization models for demand forecasting, inventory management, procurement, logistics, and operations.
• Design robust, analytics-ready Finance/Supply Chain datasets and features that power models, dashboards, and decision tools.
• Partner closely with Finance/Supply Chain leaders and operators to translate complex business problems into data science solutions that deliver measurable financial and operational impact.

Success in this role will be measured by the business value, reliability, and adoption of the models, tools, and insights you deliver across the Finance/Supply Chain organization.

A successful candidate will bring strong expertise in data science and a passion for solving complex Finance/Supply Chain and operational problems. Major responsibilities include:

Applied Modeling & Advanced Analytics for Finance/Supply Chain

• Design, build, and validate predictive models and optimization solutions for:
• Demand forecasting (short-, medium-, and long-term).
• Inventory and safety stock optimization.
• Replenishment and ordering policies.
• Logistics and transportation performance.
• Supplier performance and risk.

Data Foundations, Feature Engineering & Experimentation

• Partner with Data Engineers, Data Scientists, and Finance/Supply Chain stakeholders to design analytics-ready datasets from multiple source systems (ERP, planning systems, logistics platforms, supplier data, external signals).
• Use SQL and Python (or similar languages) to:
  • Extract, clean, and transform large, messy, real-world datasets.
  • Engineer features that capture seasonality, lead times, constraints, service levels, and cost drivers.
  • Build repeatable, production-grade data preparation workflows and pipelines.
• Implement robust data quality checks, investigate anomalies, and ensure models are built on trustworthy data.
• Design and execute back-testing, benchmarking, and controlled experiments where appropriate.

Measurement, Decision Support & Business Impact

• Quantify the financial and operational impact of models (e.g., inventory reductions, service level improvements, working capital optimization, spoilage reduction, logistics cost savings).
• Develop structured reports and dashboards (in partnership with Analytics/BI teams) to monitor:
  • Model performance and drift.
  • Key Finance/Supply Chain KPIs and their relationship to model outputs.
• Communicate results in a clear, concise, and actionable way for non-technical stakeholders, highlighting trade-offs and recommendations.
• Support scenario planning and strategic decision-making (e.g., network changes, vendor changes, sourcing strategies, resilience initiatives).

Deployment, Automation & Scaling

• Collaborate with Engineers, IT, and Finance/Finance/Supply Chain Technology teams to:
  • Integrate models into production systems and planning workflows.
  • Define and support APIs, batch processes, or user interfaces that enable model…