Royal Caribbean Group · 13 hours ago
Data Scientist - Transformation Hub
Miami, FL
Full-time
Onsite
Mid, Senior Level
3+ years expRoyal Caribbean Group is a vacation-industry leader with global brands, seeking an experienced Data Scientist for their Finance Data & Insights team. The role focuses on using advanced analytics and machine learning to optimize operations and support decision-making in the CFO organization.
Travel
No H1B
Responsibilities
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
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
Apply a variety of methods, such as: Time series forecasting, regression, and hierarchical forecasting. Machine learning models (tree-based models, ensembles, etc.). Optimization and operations research (e.g., linear/mixed-integer programming, heuristics). Simulation and scenario analysis for supply disruptions and what-if planning
Translate business questions into clear analytical problems, define success metrics, and choose appropriate methods and tools
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
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)
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 consumption. Contribute to MLOps practices for versioning, monitoring, and retraining models
Help define minimum viable products (MVPs) for new analytics and AI solutions and iteratively scale them across fleets, regions, or categories
Build strong, trusted relationships with Finance/Supply Chain leaders, planners, and operators; act as a thought partner and advisor on data-driven decisions
Facilitate working sessions to clarify requirements, interpret results, and co-design decisions, policies, or process changes enabled by analytics
Prepare and deliver presentations for both technical and executive audiences, including business cases and storytelling around trade-offs and impact
Contribute to the broader Data Analytics & AI community by sharing best practices, reusable code, and learnings from Finance/Supply Chain initiatives
Qualification
Required
Bachelor's degree in a quantitative field such as Data Science, Computer Science, Statistics, Mathematics, Industrial Engineering, Operations Research, Finance/Supply Chain Management (with strong analytics), Economics, or a related discipline; or equivalent practical experience
3+ years of hands-on experience in data science, advanced analytics, or closely related roles
2+ years of experience applying analytics or data science to Finance/Supply Chain, operations, logistics, or manufacturing problems (in industry, consulting, or equivalent experience)
Strong proficiency in Python (or R) for data analysis, modeling, and automation; experience with common libraries such as pandas, NumPy, scikit-learn (or equivalent)
Strong proficiency in SQL, including complex joins, aggregations, window functions, and performance-aware query design
Demonstrated experience building and validating predictive models and/or optimization solutions end-to-end (from data preparation to deployment or operationalization)
Experience working with relational databases and/or modern cloud data warehouses
Ability to work with large, complex, and imperfect datasets, including cleaning, feature engineering, and validation
Strong analytical and quantitative problem-solving skills, with a rigorous approach to experimentation and validation
Ability to translate ambiguous business problems into structured analytical approaches
Strong communication skills with the ability to explain technical concepts, assumptions, and trade-offs to non-technical audiences
Proven ability to manage multiple projects and priorities in a fast-paced environment
Preferred
Master's degree in a quantitative field (e.g., Operations Research, Industrial Engineering, Statistics, Applied Mathematics, Computer Science, Finance/Supply Chain Analytics)
5+ years of experience in data science/advanced analytics, with a track record of delivering measurable impact in Finance/Supply Chain or operations
Hands-on experience with: – Time series forecasting methods (ARIMA, exponential smoothing, Prophet, hierarchical forecasting). – Optimization tools and frameworks (e.g., Pyomo, PuLP, Gurobi, CPLEX, OR-Tools). – Simulation or digital twin approaches for Finance/Supply Chain
Experience with cloud platforms (Azure, AWS, or GCP) and cloud data warehouses (e.g., Snowflake, Redshift, BigQuery, Azure Synapse)
Familiarity with big data or distributed processing frameworks (e.g., Spark, Databricks)
Experience with workflow orchestration and data transformation tools (e.g., Airflow, dbt, Azure Data Factory)
Experience building or contributing to dashboards and decision-support tools in Tableau, Power BI, or similar
Exposure to MLOps practices and tools (e.g., MLflow, SageMaker, Azure ML)
Experience in industries with complex Finance/Supply Chains, such as hospitality, cruise, travel, consumer packaged goods (CPG), retail, or manufacturing
Familiarity with enterprise Finance/Supply Chain and planning systems (e.g., SAP, SAP IBP, Blue Yonder, Manhattan, Oracle, or similar)
Strong grounding in one or more of the following: – Forecasting and time series analysis. – Inventory theory and Finance/Supply Chain analytics. – Optimization and operations research. – Machine learning and statistical modeling
Demonstrates a strong capacity for learning and assimilating new tools, methods, and technologies
Curious, detail-oriented, and passionate about improving data quality, model robustness, and decision-making
Comfortable working independently while collaborating closely with cross-functional teams
Able to navigate ambiguity, reprioritize as needed, and drive projects forward with a pragmatic, impact-focused mindset
Passionate about using data and AI to improve operational performance, guest and crew experiences, and overall business value
Interest in travel, hospitality, and/or the cruise industry is a plus
Benefits
Competitive compensation and benefits package
Excellent career development opportunities
Company
Royal Caribbean Group
Royal Caribbean Group is a cruise vacation company with a global fleet of 63 ships traveling around the world.
10001+ employees
Funding
Current Stage
Public CompanyTotal Funding
$15.43BKey Investors
RCI HoldingsMorgan Stanley
2025-09-22Post Ipo Debt· $1.5B
2025-05-14Post Ipo Debt· $2.28B
2024-09-16Post Ipo Debt· $1.5B
Leadership Team
Jason Liberty
Chairman and Chief Executive Officer
Matt Denesuk
SVP, Chief AI Officer
Recent News
Morningstar.com
2026-01-16
Company data provided by crunchbase