Director, Data Science

Sea World•Miami, FL

2d•Onsite

About The Position

SeaWorld is a world-renowned leader in the themed-park and entertainment industry. Our success is built on a passion for caring for animals and a dedication to delivering positive, memorable experiences to people from around the world. Were also committed to helping ambitious people achieve their professional best. We're always seeking exceptionally skilled and knowledgeable individuals to join our team. Onsite: Miami, FL

Requirements

Expertise in AI, machine learning, and predictive modeling with a track record of deploying real-time marketing optimization solutions.
Strong experience with Databricks, Python, SQL, Spark, and cloud platforms (AWS/GCP).
Ability to translate AI-driven insights into tangible business strategies that impact revenue and guest engagement.
Experience in leading data science teams and collaborating with marketing, sales, and product teams.
Strong understanding of media optimization, attribution modeling, and real-time decisioning AI.

Responsibilities

Predictive & Prescriptive Modeling Develop, test, and operationalize predictive and prescriptive models to enable right audience, right message, right channel marketing execution: Ticket & Pass Prediction – Identify customers likely to purchase a Pass, Fun Card, Multi-Day, or Single-Day Ticket to optimize targeting and creative execution.
Guest Interest Classification – Predict whether a guest is an Animal Lover, Thrill Seeker, or Foodie to tailor marketing creative, landing pages, and post-purchase engagement.
Customer Lifetime Value (LTV) & Churn Prediction – Forecast LTV to inform Customer Acquisition Cost (CAC), prospect targeting, win-back strategies, and lapse/churn risk management.
AI-Powered Learning Platforms & Self-Service Tools Build AI-driven learning tools to empower corporate and park teams with real-time, data-driven decision-making capabilities: Causal Analysis – Develop self-serve tools to measure the impact of marketing efforts, ticket pricing, and promotions on pass sales and visitation.
Geo Lift, Market Mix Modeling & Budget Optimization – Build models to assess offer impact by channel, optimize media mix, and forecast visitation based on geo-lift experiments.
Performance Management & Anomaly Detection – Create a real-time performance tracking system in Databricks, integrating spend, impressions, clicks, and purchases with : Automated anomaly detection triggering alerts when deviations exceed a set threshold from plan, last week, or year-over-year trends.
Root cause diagnostics to enable teams to take immediate corrective action.
Customer Behavior & Sentiment Analysis – Build a queryable platform that triangulates business results, marketing performance, surveys, and social listening, enabling teams to: Use natural language queries for insights.
Support conversational commerce by analyzing web recordings, call center transcripts, and social forum discussions.
Agentic AI for Marketing & Revenue Optimization Drive agentic AI exploration, testing, and productionalization to automate real-time marketing decisions and revenue strategies: AI-Driven Media & Offer Optimization Develop AI agents that adjust channel spend in real-time to meet pass/ticket and visit goals within budget constraints.
Enable certain AI-driven offer optimizations to be auto-deployed, while others require human authorization.
Predictive Demand & Geo-Fenced Offer Automation Forecast daily and next-day attendance and trigger geo-fenced, time-sensitive offers (e.g., 4 PM-to-close tickets, animal encounter day-of offers).
AI-Powered Content & Creative Optimization Use contextual AI to auto-optimize email offers, messages, and images.
Deploy generative AI to create dynamic content variations based on guest behavior and engagement.