Associate Data Scientist
$40 - $42 per hourBrooksource
Data Science Analyst
Hybrid Role Compensation: $40 - $42 ABOUT THE ROLE 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.
EEO:
We are committed to creating an inclusive environment for all employees and applicants. We do not discriminate on the basis of race, color, religion, creed, sex, sexual orientation, gender identity or expression, national origin, ancestry, age, disability, genetic information, marital status, military or veteran status, citizenship, pregnancy (including childbirth, lactation, and related conditions), or any other protected status in accordance with applicable federal, state, and local laws.
Benefits & Perks:
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.
Pay Disclaimer:
The pay range for this job level is a general guideline only and not a guarantee of compensation or salary. Additional factors considered in extending an offer include (but are not limited to) responsibilities of the job, education, experience, knowledge, skills, and abilities, as well as internal equity, alignment with market data, applicable bargaining agreement (if any), or other law.
Vacancy posted 16 hours ago
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