Data Scientist
Royal Caribbean Group
full-time
Posted on:
Location Type: Office
Location: Miami • Florida • United States
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About the role
- Support cross-functional AI/ML initiatives across Royal Caribbean Group.
- Contribute to the design, development, and delivery of robust production-grade models and analytical solutions.
- 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.
- Partner with data engineers to define dataset requirements, validate data quality, and ensure pipeline reliability.
- Design A/B tests, multivariate tests, and uplift experiments aligned with statistical rigor.
- Create clear, actionable presentations, readouts, and memos that translate analytics into business impact.
- Maintain fluency with emerging ML algorithms, cloud tooling, vector databases, responsible AI guidelines, and Azure ecosystem updates.
Requirements
- Bachelor's Degree in business or a technology-related area of study preferred
- 2+ years of experience as a Product Owner or Product Manager in eCommerce or 4+ years of proven working experience in digital marketing
- Experience with agile software development processes, requirements management, and project management using JIRA/Confluence or similar Agile collaboration tools
- Experience in working with CRM teams to execute a complex, highly segmented, and personalized email communication strategy
- Travel Industry eCommerce experience preferred
- Bachelor’s or Master’s degree in Data Science, Computer Science, Statistics, Applied Mathematics, Engineering, or related field.
- 2–4 years of hands-on experience designing, building, and deploying ML models in a business environment.
- Experience working with cloud data platforms or ML infrastructure (Azure preferred).
- Proficiency in Python and ML libraries such as scikit-learn, XGBoost, LightGBM, pandas, NumPy, and statsmodels.
- Solid SQL skills and familiarity with distributed data tools (Spark, Databricks).
- Understanding of classical statistics: hypothesis testing, confidence intervals, regression diagnostics, ANOVA, probability theory.
- Soft Skills: Strong analytical and critical-thinking capabilities with structured problem-solving ability.
- Clear, concise communication across technical and non-technical audiences.
- Ability to manage multiple priorities, adapt to evolving requirements, and maintain high attention to detail.
Benefits
- competitive compensation and benefits package
- excellent career development opportunities
Applicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills & Tools
machine learningdeep exploratory data analysisfeature engineeringpredictive modelingregressionclassificationclusteringtime-series forecastingSQLclassical statistics
Soft Skills
analytical skillscritical thinkingstructured problem-solvingclear communicationattention to detailadaptabilityproject managementcollaborationpresentation skillsbusiness impact translation
Certifications
Bachelor's DegreeMaster's Degree