SeaWorld Entertainment, Inc.

Director, Data Science

SeaWorld Entertainment, Inc. • $120K — $150K *
Miami, FL 33186In-Person
Consumer Technology
8 - 10 years of experience
Reposted Today
Be an Early Applicant
Job Overview by Ladders

Qualifications

  • 8+ years of experience in data science and marketing analytics
  • Master's degree in Analytics or related field
  • Proven expertise in AI, machine learning, and predictive modeling
  • Strong experience with Databricks, Python, SQL, Spark, and cloud platforms
  • Ability to translate data insights into business strategies
  • Experience leading data science teams and collaborating cross-functionally

Responsibilities

  • Develop and operationalize predictive models for targeted marketing
  • Build AI-driven learning platforms for data-driven decision-making
  • Create real-time performance tracking systems in data platforms
  • Automate marketing decisions using agentic AI technologies
  • Conduct customer behavior and sentiment analysis for insights
  • Optimize channel spend and marketing offers with AI

Benefits

  • Paid Time Off
  • Complimentary Park Tickets and Passes
  • Park Discounts on Food and Merchandise
  • Medical, Dental, and Vision Insurance
  • 401K Retirement plan
  • Tuition Reimbursement
  • Employee Assistance Program
Full Job Description
Onsite: Miami, FL

Key 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.


What We're Looking For
  • 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.


The perks of the position:
  • Paid Time Off
  • Complimentary Park Tickets and Passes
  • Park Discounts on Food and Merchandise
  • Medical, Dental, and Vision Insurance
  • 401K Retirement plan
  • Voluntary Insurance
  • Life Insurance
  • Disability Benefits
  • Tuition Reimbursement
  • Dependent and Health Care Flexible Spending Accounts
  • Employee Assistance Program
  • Legal Assistance Plan


About SeaWorld Entertainment, Inc.

SeaWorld Entertainment, Inc. is a theme park and entertainment company that operates marine mammal parks, oceanariums, animal theme parks, and water parks. The company owns and operates twelve parks located across the United States. SeaWorld parks feature live entertainment, rides, and animal exhibits. The company is also involved in conservation efforts and animal rescue operations. SeaWorld Entertainment, Inc. was founded in 1959 and is headquartered in Orlando, Florida.
Learn more about SeaWorld Entertainment, Inc.
Size
2,800 employees
Market Cap
$3.2 billion
Industry
Hospitality & Recreation
Net Income
-$312.3 million
5 Year Trend
+2.3%
Revenue
$431.7 million
NASDAQ
SEAS
* Ladders Estimates

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