Data Scientist
Position Summary
We are seeking a Data Scientist to lead cross-functional AI/ML initiatives and drive our enterprise-wide AI vision and strategy. This role is a bridge between tactical execution and long-term strategic planning, requiring a visionary who can work independently and collaboratively with data analytics professionals across and outside Royal Caribbean Group to deliver transformative AI/ML solutions. The Data Scientist will frequently interface with senior stakeholders, providing thought leadership and regular updates on key analytics initiatives. This position demands top-tier technical expertise in machine learning & generative AI, combined with exceptional written and oral communication skills. The ideal candidate is a proven leader who pairs expert-level modeling and software engineering skills with outstanding stakeholder management and strategic program leadership.
Essential Responsibilities
- Own end-to-end model development for pricing, demand forecasting, and elasticity estimation; productionize models in Azure ML and Databricks.
- Implement prescriptive analytics through optimization with Linear Programming, Mixed Integer Programming or Reinforcement Learning.
- Implement and maintain feature stores, model monitoring workflows, and drift checks using MLflow (metrics, alerts, lineage).
- Design and execute A/B tests or quasi-experiments to measure revenue, pricing uplift, and PCP attach rate impact.
- Apply SHAP/LIME and other model interpretability tools to explain drivers of model behavior to Revenue Management partners.
- Contribute to CI/CD workflows (Azure DevOps), support data contracts with Data Engineering, and develop scalable API and batch-serving patterns.
- Communicate insights, assumptions, risks, and trade-offs in clear, concise, and executive-ready narratives.
Qualifications / Knowledge / Skills
- 2–4 years of hands-on Data Science experience delivering production-grade ML solutions.
- Proficiency in Python (scikitlearn, XGBoost), Spark/Delta, SQL, Azure ML, Databricks, and MLflow; familiarity with PyTorch or TensorFlow is a plus.
- Strong understanding of experimental design, statistical testing, and causal inference basics.
- Ability to translate technical concepts into actionable business insights; skilled in stakeholder alignment and cross-functional communication.
Power Skills
- Action Oriented
- Collaborates Effectively
- Communicates Effectively
- Drives Results
- Situational Adaptability