Job Summary:

We seek candidates for roles at multiple levels within the Decision Science team. The specific job level for an individual candidate will be determined based on their education, prior experience, and demonstrated technical and leadership proficiencies.

The Decision Science team focuses on creating innovative mathematical models to inform business decision making through data. The team is interested in all fields related to data science, with emphasis on statistics, operations research, econometrics, and machine learning.

The Decision Science team resides within the Disney Decision Science + Integration (DDSI) organization. DDSI provides internal consulting services for clients across The Walt Disney Company, including Disney Parks, Experiences and Products (covering Parks & Resorts, Signature Experiences, and Consumer Products, Games and Publishing) and Disney Media & Entertainment Distribution (covering content from Studios, General Entertainment and Sports).

The DDSI team sits at the intersection of business strategy, advanced analytics, and technology integration to help our partners explore opportunities for analytics, shape business decisions, and drive value. Our work includes conceptualizing new solutions, solution design and development, implementation and integration with business processes, and ongoing business support.

Responsibilities:

• Achieve business goals and objectives—Research and develop decision science models and act as a consultant to all business units within The Walt Disney Company
• Pursue innovation—Conduct research on analytical techniques and translate that research into usable and sustainable solutions for users
• Put your skills to the test—Perform data collection and data mining, and build state-of-the-art decision science algorithms, tools, and systems
• Drive value—Model and analyze revenue management and pricing related issues using various mathematical, statistical, and simulation techniques
• Tell the story—Present science results to business partners and clients
• Support a global and enterprise-wide mission—Identify and apply best practices in the field of advanced analytics for multiple businesses such as theme parks and resorts (e.g. Walt Disney World), Disney Cruise Line, media (e.g. ABC, ESPN), movies (e.g. Walt Disney Animation Studios), live shows (e.g. Disney on Broadway), and retail (e.g. shopDisney)

Basic Qualifications:

• Must exhibit competence in at least one of the following four analytical fields, inclusive of topics as noted:
  • Statistics (two or more topics):
    • Bayesian statistics
    • Generalized linear models
    • Mixture models
    • Nonparametric regression
    • Structural equation models
    • Time series (state space models, ARIMA, etc.)
  • Optimization (at least one topic):
    • Decision analysis or multiple criteria decision making
    • Mixed-integer optimization
    • Nonlinear optimization
    • Stochastic optimization
    • Discrete-event simulation and stochastic models
  • Econometrics (two or more topics):
    • Generalized method of moments
    • Instrumental variables
    • Limited dependent variables
    • Panel data
    • Simultaneous equations models
  • Machine learning (two or more topics):
    • Boosting
    • CART
    • Clustering
    • Graphical models
    • Neural networks
    • Random forests
    • Reinforcement learning
    • Support vector machines
• Must exhibit competence in at least one computing topic:
  • General computing (Python, Java, C, C++, etc.)
  • Statistical computing (R, SAS, etc.)
  • Scientific computing (Julia, MATLAB, etc.)
• Roles beyond the entry level require the ability to work with little guidance on science methodologies and modeling approaches, based on sound business acumen, and to provide peer leadership to junior colleagues
• Higher roles require the ability to work concurrently across lines of business or functional areas, to direct the design and development of advanced analytical models, or to provide project leadership to ensure successful implementation of solutions across all project phases

Preferred Qualifications:

• Proven knowledge of revenue management context, including demand forecasting, resource allocation, and pricing

Required Education

• Master’s or Ph.D. degree in Statistics, Operations Research, Industrial Engineering, Mathematics, Machine Learning, Econometrics, or related field