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Director, Finance - Data Science & Attendance Forecasting - NBC Universal
Data Scientist
Lead the design and deployment of advanced predictive models to forecast attendance and ticket revenue, driving financial strategy across multiple theme park locations using Python, SQL, and machine learning techniques.
About the role
Key Responsibilities
- Design, develop, and validate predictive and machine learning models for attendance and ticketing revenue forecasting across UDX, UOR, USH, USJ, and UBR.
- Extract and analyze structured and unstructured guest behavior data to uncover insights on visitation patterns by sales channel, origin, and ticket type.
- Collaborate with finance and operations teams to translate model outputs into actionable financial strategies and revenue optimization plans.
- Lead model performance monitoring, ensuring accuracy and scalability, and iterate on models based on new data and business requirements.
- Communicate findings and recommendations to senior leadership through clear visualizations and executive summaries.
Requirements
- Extensive experience (10+ years) in data science, predictive modeling, and financial forecasting within a large enterprise or theme park environment.
- Proficiency in Python, SQL, and machine learning libraries (scikit-learn, TensorFlow, PyTorch).
- Strong analytical skills with a proven track record of turning complex data into strategic business insights.
- Excellent communication skills, able to present technical concepts to non‑technical stakeholders.
- Leadership experience managing cross‑functional teams and driving data‑driven decision making.
Skills
pythonmachine learningsqldata analysis