Senior Analyst, Brand Analytics

Royal Caribbean Cruises Ltd•Miami, FL

8d•Onsite

About The Position

The Senior Analyst, Brand Analytics plays a pivotal role in driving commercial decision-making for the Silversea brand across global markets. This role is responsible for developing and maintaining processes for accurate data collection, modelling, analysis, visualization, and reporting. Success in this position requires strong analytical capabilities, a collaborative mindset, and the ability to communicate insights effectively across the organization. The ideal candidate is data-driven, curious, and skilled at identifying trends and translating them into actionable business strategies.

Requirements

Bachelor’s degree in Analytics, Mathematics, Statistics, Business, Finance, or a related field.
Minimum 3 years of experience in commercial planning, budgeting, forecasting, and financial modeling in fast-paced environments.
Proven ability to deliver results with consistency, precision, and timeliness.
Strong experience designing, building, and reviewing financial models for strategic initiatives.
Ability to quickly learn and adapt to new challenges and business needs.
Deep understanding of financial KPIs and business performance metrics.
Advanced proficiency in Microsoft Office applications and SQL Server.
Excellent communication and stakeholder engagement skills.
Ability to influence across all levels of the organization.
Highly motivated, results-driven team player with a proactive, positive attitude.
Comfortable working in a dynamic, fast-paced environment and embracing challenges.

Nice To Haves

Experience working in international, matrix-structured organizations is a plus.

Responsibilities

Explain how metrics align with business objectives and identify key impact levers for decision-making.
Break down complex problems into clear hypotheses and select appropriate analytical methods.
Conduct scenario analysis to quantify ranges, highlight drivers, and recommend next steps.
Recommend metric refinements and validate denominators, time windows, and filters to ensure accuracy.
Propose roadmap initiatives based on insights and evolving partner needs.
Build reusable SQL queries and data views, addressing edge cases and late-arriving data.
Apply statistical and machine learning methods (e.g., regression, classification, clustering, causal inference) and validate assumptions.
Design role-based dashboards with parameters, drill-downs, and alerts to enhance usability.
Implement robust data validation checks, back-tests, and regression checks to ensure quality.
Translate analysis into clear business implications and propose actionable, testable recommendations.
Manage scope and expectations effectively, negotiating trade-offs when necessary.
Collaborate with operations and engineering teams to resolve data issues and ensure smooth delivery.
Tailor communication to diverse audiences, anticipating objections and aligning stakeholders.
Mentor junior analysts by modeling best practices and providing constructive feedback.
Prioritize high-impact tasks and defer low-value work to maximize efficiency.
Create documentation such as read-me files, data dictionaries, and run-books for transparency.
Lead enablement sessions and iterate based on feedback to drive adoption of analytics solutions.
Foster a data-driven culture by introducing lightweight rituals (e.g., show-and-tell sessions, tips & tricks).
Suggest pragmatic improvements that advance the analytics vision and operating model.