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About This Role
The Analyst, Consumer AI Analytics \& Insights is responsible for measuring, analyzing, and optimizing the performance and business impact of Consumer AI initiatives. This role serves as the analytical engine of the Consumer AI team, providing data\-driven insights that support AI strategy, use\-case prioritization, solution performance, adoption, and value realization.
The Analyst partners closely with the Director, Consumer AI and Manager, Consumer AI Solutions to identify AI opportunities, evaluate initiative performance, develop KPI frameworks, conduct experimentation, and communicate outcomes to stakeholders. This role combines analytics, business intelligence, customer insights, and AI performance measurement to help ensure Consumer AI investments deliver meaningful guest, commercial, and operational value.
Essential Functions:
AI Analytics, Measurement, and Insights
- Develop KPI frameworks and measurement plans for AI initiatives
- Analyze customer, digital, loyalty, marketing, ecommerce, and operational data to identify AI opportunities
- Create dashboards and scorecards tracking AI adoption, effectiveness, utilization, and business value
- Measure revenue impact, productivity improvements, containment rates, customer satisfaction, and operational efficiencies
- Perform trend analysis to identify optimization opportunities and emerging patterns
- Support AI performance measurement from pilot through production deployment
AI Evaluation, Testing, and Optimization
- Support user acceptance testing (UAT), pilot programs, and solution validation activities
- Document test plans, testing results, defects, risks, and enhancement recommendations
- Assist in evaluating AI\-generated outputs for quality, accuracy, relevance, consistency, and compliance
- Coordinate stakeholder feedback collection, issue tracking, and resolution monitoring
- Support prompt testing, solution evaluations, model assessments, and AI performance benchmarking
- Design and support A/B testing, pilot measurement, and experimentation frameworks
- Analyze adoption trends, engagement patterns, containment rates, escalation behavior, and feature utilization
- Evaluate effectiveness, intent recognition accuracy, resolution effectiveness, and customer experience outcomes
- Provide recommendations to improve AI experiences, workflows, personalization, and business results
Executive Reporting and Business Intelligence
- Develop executive scorecards, dashboards, and recurring AI performance reports
- Create presentations and insights for leadership reviews, roadmap discussions, and AI governance forums
- Monitor progress against AI success metrics and strategic objectives
- Support the creation of quarterly business reviews and AI value realization updates
- Translate complex data into clear business insights and actionable recommendations
Governance, Documentation, and Portfolio Support
- Support Responsible AI measurement and governance reporting
- Maintain documentation related to AI initiatives, metrics, assumptions, and outcomes
- Assist with roadmap planning, prioritization, and portfolio tracking processes
- Support operating model development and AI initiative intake processes
- Maintain data integrity and reporting standards across AI programs
Performs Other Duties as Assigned
- Support strategic AI initiatives and special projects
- Assist with departmental planning, reporting, and operational activities
- Contribute to ongoing development of Consumer AI capabilities
Knowledge, Skills \& Abilities:
- Scope: This role serves as the primary analytics and insights resource for the Consumer AI team. The Analyst is responsible for measuring the effectiveness of AI initiatives, identifying opportunities through data analysis, and helping leadership make informed decisions regarding AI investments, priorities, and optimization opportunities. Success is measured through the quality of insights delivered, accuracy of reporting, identification of high\-value opportunities, and the measurable business impact of AI programs.
- Problem solving: Ability to analyze large and complex datasets, identify trends and patterns, develop data\-driven recommendations, and translate findings into actionable business insights. Demonstrated capability to work through ambiguity, evaluate competing hypotheses, and solve business problems through analytical approaches.
- Impact: Directly influences AI investment decisions, roadmap prioritization, solution optimization, and value realization efforts. Recommendations from this role impact customer experience improvements, revenue growth opportunities, operational efficiencies, and the overall effectiveness of Consumer AI initiatives
- Leadership: Leads through analytical expertise, business insight, and influence. Partners effectively with business, product, technology, analytics, and customer experience teams to support data\-driven decision\-making and continuous improvement.
Essential/Minimum qualifications:
- Bachelor's degree in Business, Analytics, Information Systems, Marketing, Data Science, Computer Science, or related field
- Strong analytical and problem\-solving skills
- Experience working with data analysis, reporting, project coordination, or business analysis activities
- Strong written and verbal communication skills
- Ability to work effectively with cross\-functional business and technology teams
Essential experience required:
- 2\+ years of experience in business analysis, analytics, digital product support, project management, consulting, technology, or related fields
- Experience gathering requirements, documenting processes, and supporting cross\-functional initiatives
- Experience using reporting and visualization tools such as Power BI, Tableau, Excel, or equivalent
- Experience developing reports, dashboards, KPIs, and business insights
- Familiarity with AI, Generative AI, digital products, automation, analytics, or emerging technology initiatives preferred
- Experience supporting testing, quality assurance, or user acceptance testing activities preferred
- Strong proficiency with Microsoft Office applications, particularly Excel and PowerPoint
- Ability to manage multiple priorities in a fast\-paced and evolving environment
- Experience preparing executive presentations, status updates, and business recommendations preferred
Preferred Qualifications:
- Experience working with Microsoft Copilot, Copilot Studio, Power Platform, or AI\-enabled business tools
- Experience supporting digital transformation, automation, or innovation initiatives
- Basic understanding of prompt engineering, AI governance, and responsible AI concepts
- Experience in ecommerce, marketing, loyalty, customer experience, travel, hospitality, or cruise industries preferred
Travel: Less than 25% with shipboard travel likely
Work Conditions:Work primarily in a climate\-controlled environment with minimal safety/health hazard potential.
Physical Demands. Must be able to remain in a stationary position at a desk and/or computer for extended periods of time.
This position is classified as “in\-office.” As an in\-office role, it requires employees to work from a designated Carnival office in South Florida Monday through Thursday each week. Employees may work from their homes on Fridays. Candidates must be located in (or willing to relocate to) the Miami/Ft. Lauderdale area.
Offers to selected candidates will be made on a fair and equitable basis, taking into account specific job\-related skills and experience.
At Carnival, your total rewards package is much more than your base salary. All non\-sales roles participate in an annual cash bonus program, while sales roles have an incentive plan. Director and above roles may also be eligible to participate in Carnival’s discretionary equity incentive plan. Plus, Carnival provides comprehensive and innovative benefits to meet your needs, including:
- Health Benefits:
+ Cost\-effective medical, dental and vision plans
+ Employee Assistance Program and other mental health resources
+ Additional programs include company paid term life insurance and disability coverage
- Financial Benefits:
+ 401(k) plan that includes a company match
+ Employee Stock Purchase plan
- Paid Time Off
+ Holidays – All full\-time and part\-time with benefits employees receive days off for 8 company\-wide holidays, plus 2 additional floating holidays to be taken at the employee’s discretion.
+ Vacation Time – All full\-time employees at the manager and below level start with 14 days/year; director and above level start with 19 days/year. Part\-time with benefits employees receive time off based on the number of hours they work, with a minimum of 84 hours/year. All employees gain additional vacation time with further tenure.
+ Sick Time – All full\-time employees receive 80 hours of sick time each year. Part\-time with benefits employees receive time off based on the number of hours they work, with a minimum of 60 hours each year.
- Other Benefits
+ Complementary stand\-by cruises, employee discounts on confirmed cruises, plus special rates for family and friends
+ Personal and professional learning and development resources including tuition reimbursement
+ On\-site Fitness center at our Miami campus
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About Us
At Carnival Cruise Line, our mission is to consistently deliver safe, fun, and memorable vacations at a great value. As the world’s most popular cruise line, we offer a variety of unique experiences across our fleet, ensuring that every voyage is filled with excitement and discovery. From world\-class entertainment and dining to exploring stunning destinations, we create lasting memories for our guests while maintaining a dedication to the places we visit and the lives we touch.
Join us and embark on a career that offers not only the chance to grow professionally but also the opportunity to be part of a global community that makes a difference.
In addition to other duties/functions, this position requires full commitment and support for promoting ethical and compliant culture. More specifically, this position requires integrity, honesty, and respectful treatment of others, as well as a willingness to speak up when they see misconduct or have concerns.
Carnival Corporation and Carnival Cruise Line is an equal employment opportunity/affirmative action employer. In this regard, it does not discriminate against any qualified individual on the basis of sex, race, color, national origin, religion, sexual orientation, age, marital status, mental, physical or sensory disability, or any other classification protected by applicable local, state, federal, and/or international law.
https://www.dol.gov/sites/dolgov/files/WHD/legacy/files/eppac.pdf
https://www.dol.gov/sites/dolgov/files/WHD/legacy/files/fmlaen.pdf
Role Details
About This Role
AI/ML Engineers build and deploy machine learning models in production. They work across the full ML lifecycle: data pipelines, model training, evaluation, and serving infrastructure. The role has evolved significantly over the past two years. Where ML Engineers once spent most of their time on model architecture, the job now tilts heavily toward inference optimization, cost management, and integrating LLM capabilities into existing systems. Companies want engineers who can ship production systems, and the experimenter-only role is fading fast.
Day-to-day, you're writing training pipelines, debugging data quality issues, setting up evaluation frameworks, and figuring out why your model performs differently in staging than it did on your dev set. The best ML engineers are obsessive about reproducibility and measurement. They instrument everything. They know that a model is only as good as the data feeding it and the infrastructure serving it.
Across the 4,317 AI roles we're tracking, AI/ML Engineer positions make up 70% of the market. At Carnival Cruise Line, this role fits into their broader AI and engineering organization.
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
What the Work Looks Like
A typical week might include: debugging a data pipeline that's silently dropping 3% of training examples, running A/B tests on a new model version, writing documentation for a feature flag system that lets you roll back model deployments, and reviewing a junior engineer's PR for a new evaluation metric. Meetings tend to be cross-functional since ML touches product, engineering, and data teams.
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
Skills Required
Python and PyTorch dominate the requirements. Most roles expect experience with cloud platforms (AWS, GCP, or Azure) and familiarity with ML frameworks like TensorFlow or JAX. RAG (Retrieval-Augmented Generation) has become a top-3 skill requirement as companies integrate LLMs into their products. Docker and Kubernetes show up in about a third of postings, reflecting the production focus of the role.
Beyond the core stack, employers increasingly want experience with experiment tracking tools (MLflow, Weights & Biases), feature stores, and vector databases. Fine-tuning experience is valuable but less common than you'd think from reading Twitter. Most production LLM work is RAG and prompt engineering, not fine-tuning. If you have both, you're in a strong position.
Companies that are serious about AI/ML hiring tend to post specific infrastructure details in the job description: the frameworks they use, their model serving stack, their data pipeline tools. Vague postings that just say 'ML experience required' without specifics are often companies that haven't figured out what they need yet.
Compensation Benchmarks
AI/ML Engineer roles pay a median of $214,900 based on 6,420 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $194,400.
Across all AI roles, the market median is $215,000. Top-quartile compensation starts at $266,300. The 90th percentile reaches $320,790. For comparison, the highest-paying categories include AI Safety ($287,500) and Research Engineer ($272,100). By seniority level: Entry: $110,000; Mid: $194,400; Senior: $227,400; Director: $274,554; VP: $241,000.
Carnival Cruise Line AI Hiring
Carnival Cruise Line has 1 open AI role right now. They're hiring across AI/ML Engineer. Based in Miami, FL, US.
Location Context
Across all AI roles, 15% (635 positions) offer remote work, while 3,657 require on-site attendance. Top AI hiring metros: New York (1,650 roles, $220,000 median); San Francisco (1,335 roles, $265,000 median); Los Angeles (708 roles, $214,112 median).
Career Path
Common paths into AI/ML Engineer roles include Data Scientist, Software Engineer, Research Engineer.
From here, career progression typically leads toward ML Architect, AI Engineering Manager, Principal ML Engineer.
The fastest path into ML engineering is through software engineering with a self-directed ML education. A CS degree helps, but production engineering skills matter more than academic credentials. Build something that works, deploy it, and measure it. That portfolio project is worth more than a Coursera certificate. For career growth, the fork comes around the senior level: go deep on technical complexity (staff/principal track) or move into managing ML teams.
What to Expect in Interviews
Expect system design questions around ML pipelines: how you'd build a training pipeline for a specific use case, handle data drift, or design A/B testing infrastructure for model deployments. Coding rounds typically involve Python, with emphasis on data manipulation (pandas, numpy) and algorithm implementation. Take-home assignments often ask you to build an end-to-end ML pipeline from raw data to deployed model.
When evaluating opportunities: Companies that are serious about AI/ML hiring tend to post specific infrastructure details in the job description: the frameworks they use, their model serving stack, their data pipeline tools. Vague postings that just say 'ML experience required' without specifics are often companies that haven't figured out what they need yet.
AI Hiring Overview
The AI job market has 4,317 open positions tracked in our dataset. By seniority: 138 entry-level, 2,071 mid-level, 1,655 senior, and 453 leadership roles (Director, VP, C-Level). Remote roles make up 15% of the market (635 positions). The remaining 3,657 roles require on-site or hybrid attendance.
The market median for AI roles is $215,000. Top-quartile compensation starts at $266,300. The 90th percentile reaches $320,790. Highest-paying categories: AI Safety ($287,500 median, 34 roles); Research Engineer ($272,100 median, 227 roles); AI Engineering Manager ($244,000 median, 23 roles).
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
The AI Job Market Today
The AI job market spans 4,317 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (3,004), Data Scientist (345), AI Software Engineer (309). These three account for the majority of open positions, though smaller categories often have higher per-role compensation because of specialized skill requirements.
The seniority mix tells a story about where AI teams are in their maturity. Entry-level roles (138) are outnumbered by mid-level (2,071) and senior (1,655) positions, reflecting that most companies are past the 'build a team from scratch' phase and need experienced engineers who can ship production systems. Leadership roles (Director, VP, C-Level) total 453 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 15% of all AI roles (635 positions), with 3,657 requiring on-site or hybrid attendance. The remote share has stabilized after the post-pandemic correction. Senior and specialized roles (Research Scientist, ML Architect) are more likely to be remote-eligible than entry-level positions, partly because experienced hires have more negotiating power and partly because these roles require less hands-on mentorship.
AI compensation is structured in clear tiers. The market median sits at $215,000. Top-quartile roles start at $266,300, and the 90th percentile reaches $320,790. These figures include base salary with disclosed compensation. Total compensation (including equity, bonuses, and sign-on) runs 20-40% higher at companies that offer those components.
Category matters for compensation. AI Safety roles lead at $287,500 median, while Prompt Engineer roles sit at $145,000. The spread between highest and lowest-paying categories reflects the premium on specialized technical skills versus broader analytical roles.
The most in-demand skills across all AI postings: Python (2,249 postings), Aws (1,224 postings), Azure (938 postings), Rag (915 postings), Gcp (660 postings), Pytorch (640 postings), Prompt Engineering (624 postings), Kubernetes (559 postings). Python dominates, appearing in the vast majority of role descriptions regardless of category. Cloud platform experience (AWS, GCP, Azure) is the second most common requirement. The newer entrants to the top skills list (RAG, vector databases, LLM APIs) reflect the shift from traditional ML toward generative AI applications.
Frequently Asked Questions
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