Data Scientist - Transformation Hub

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.
• 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.

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 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.

Collaboration, Communication & Change Management

• 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.

• 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).

Technical skills:

• 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.

General skills:

• 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.

In addition to the basic qualifications, the ideal candidate will have:

• 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.

Knowledge, Skills and Attributes:

• 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.

Agency and Third-Party Submissions: Please note this is a direct search by the Company, and applications through agencies and other third parties will not be accepted, nor will fees be paid for unsolicited resumes. Any unsolicited resumes will be considered the Company's property.

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.