Data Science Analyst

Royal Caribbean Group is seeking a Data Science Analyst to support end-to-end data science delivery by translating business questions into actionable analyses, model components, and production-ready outputs. This role emphasizes ownership of delivered business value-framing the right problems, building and validating machine learning, optimization, and GenAI solutions, partnering on deployment, monitoring performance, and driving adoption in production. The ideal candidate combines statistical and machine learning depth with practical business judgment, strong stakeholder partnership, and the ability to convert analytical work into measurable outcomes rather than isolated prototypes. The position may require regular domestic or international travel and work in both office and shipboard environments. WHAT YOU’LL DO

• Frame high-impact business problems for analytics and supervised model delivery, defining clear decision owners, baseline metrics, adoption paths, and expected value tied to decision support, operational visibility, and automation.
• Develop and validate predictive models (forecasting, propensity, classification, ranking) using Python, scikit-learn, XGBoost, LightGBM, CatBoost, and Databricks feature workflows to support production decisions.
• Build prescriptive analytics solutions, including recommendation, simulation, and optimization models using MILP, heuristics, dynamic programming, or scenario modeling to improve operational and commercial outcomes.
• Design and implement GenAI workflows leveraging GPT-class models, Azure AI Foundry, RAG, embeddings, prompt engineering, and evaluation routines to enhance business productivity and workflow automation.
• Design and evaluate statistical experiments (A/B tests, quasi-experiments, causal analyses, bootstrap methods, non-parametric tests) to measure the impact of model or process changes and determine measurable lift.
• Apply explainability techniques (e.g., SHAP, sensitivity analysis, model diagnostics, error analysis) to ensure model transparency, stakeholder understanding, and trust in model-driven decisions.
• Partner with AI Engineering to deploy models and analytical applications through Databricks, Azure ML, MLflow, APIs, or containerized services, retaining accountability for business value and model behavior.
• Monitor production models for accuracy, drift, bias, adoption, latency, cost, and business KPIs; trigger retraining, recalibration, or process changes as needed to maintain performance and value realization.
• Collaborate with business, product, operations, AI Engineering, and data engineering teams to convert model outputs into decisions, workflows, incentives, and measurable adoption.

• Bachelor’s or Master’s degree in Data Science, Statistics, Computer Science, Operations Research, Engineering, Economics, or a related quantitative field, or equivalent practical experience.
• Demonstrated experience delivering ML, optimization, experimentation, or GenAI solutions in production or business decisioning contexts, with a focus on measurable business impact.
• Hands-on experience with Python, scikit-learn, XGBoost, LightGBM, CatBoost, PyTorch or TensorFlow, and model evaluation workflows for production-grade use cases.
• Experience with MILP solvers, simulation, scenario planning, dynamic programming, heuristics, or prescriptive analytics methods applied to real business decisions.
• Experience with Azure AI Foundry, GPT-class models, RAG, embeddings, prompt engineering, evaluation, and safe use of GenAI for decision support or workflow automation.
• Advanced use of Databricks, Spark, SQL, feature pipelines, data quality checks, and reproducible analytical workflows for large-scale data science delivery.
• Experience with MLflow, Azure ML, model registries, CI/CD, monitoring, retraining, and production handoff practices to ensure reliability after launch.
• Strong Python engineering practices, Git workflows, testing, packaging, notebooks-to-production discipline, API development, and collaboration with AI Engineering for deployment readiness.
• Clear communication skills with data scientists, product owners, analysts, and business stakeholders, including the ability to explain model logic, uncertainty, tradeoffs, risks, and recommended decisions in business terms.

PHYSICAL DEMANDS

The physical demands described here are representative of those requirements employees must meet to perform the essential functions of this job with or without reasonable accommodations. While performing job functions, the employee is regularly required to sit and stand; write, review and type reports; compile data; operate a PC; communicate and listen; and assess information. The employee may move about the office complex, travel to other office locations, and lift, push, pull, or move 10-15 pounds. The employee is occasionally required to walk to the dock and ascend/descend the vessel. This position may require regular domestic or international travel. Visual requirements include distant, close, and color vision, as well as the ability to adjust focus.

Brooksource offers competitive medical, dental, vision, Health Savings Account, Dependent Care FSA, and supplemental coverage with plans that can fit each employee’s needs. We offer a 401k plan that includes a company match and is fully vested after you become eligible, paid time off, sick time, and paid company holidays. We also offer an Employee Assistance Program (EAP) that provides services like virtual counseling, financial services, legal services, life coaching, etc.

Brooksource, Medasource, and Calculated Hire are part of the Eight Eleven Group family of companies and operate under Eight Eleven Group, LLC. All employees receive the same benefits, policies, and terms of employment.