Data Scientist

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.

The Royal Caribbean Group’s AI & Analytics Team has an exciting career opportunity for a full-time Data Scientist reporting to Senior Manager, Data Analytics & AI. The position is onsite and based in Miami, Florida. The position is also not eligible for work authorization sponsorship.

The Data Scientist plays a critical role in supporting cross-functional AI/ML initiatives across Royal Caribbean Group. This position contributes to the design, development, and delivery of robust production-grade models and analytical solutions. The role blends statistical analysis, machine learning engineering, experimentation, and business partnership to drive measurable value. Candidates should have strong foundations in ML, data wrangling, statistics, and software-centric approaches to analytics.

The role requires curiosity, disciplined problem solving, and the ability to translate ambiguous business questions into structured analytical tasks. Data Scientists are expected to interface with business stakeholders, data engineers, product owners, and senior DS talent while demonstrating ownership of deliverables and continuous professional growth.

• Machine Learning & Analytics Execution
• Perform deep exploratory data analysis to identify patterns, anomalies, data quality issues, and signal strength.
• Conduct end-to-end feature engineering including feature selection, encoding, scaling, transformation, leakage prevention, and feature importance evaluations.
• Build and tune predictive models using regression, classification, clustering, ensemble methods, and time-series forecasting.
• Apply model validation techniques such as cross-validation, bootstrapping, hyperparameter search, and error analysis.
• Implement explainability tools (e.g., SHAP, LIME, partial dependence plots) to support interpretability and trust.
• Ensure ML artifacts follow reproducibility, documentation, and version control standards (via MLFlow / Git Hub).
• Collaboration & Delivery
• Partner with data engineers to define dataset requirements, validate data quality, and ensure pipeline reliability.
• Participate in developing model training, inference, scoring, and monitoring pipelines using Azure ML and Databricks.
• Follow MLOps best practices including Git-based versioning, CI/CD for model code, experiment tracking (MLflow), and model lineage documentation.
• Work closely with product managers and business partners to refine requirements, align on success metrics, and operationalize analytical outputs.
• Contribute to solution design reviews, architectural discussions, and integration planning.
• Support the design and deployment of dashboards, APIs, and reporting interfaces used by downstream teams. This includes Optimization Engines, NLP/Embeddings, Generative AI Agents, and front-end user applications (e.g. Container Apps and experience with tools like Streamlit/Dash/Flask/FastAPI).
• Experimentation & Validation
• Design A/B tests, multivariate tests, and uplift experiments aligned with statistical rigor.
• Conduct power analysis, define sample sizes, and ensure proper randomization and control matching.
• Utilize quasi-experimental methods (e.g., difference-in-differences, synthetic controls, propensity scoring) when randomized tests are not feasible.
• Evaluate experiment outcomes through causal inference, significance testing, lift calculations, and behavioral segmentation.
• Diagnose experiment failures, identify bias risks, and refine experiment protocols.
• Contribute to reusable experiment templates, calculators, documentation, and internal best-practice playbooks.
• Collaborate with cross-functional teams to validate real-world model performance and align on adjustments.
• Communication
• Create clear, actionable presentations, readouts, and memos that translate analytics into business impact.
• Build visualizations using tools such as…