Rarefied talent in big data technology and analytics

Decision Science Technical Manager

Disney Parks & Resorts

Job Description

Create innovative scientific models and data-driven decision support tools as a member of our Decision Science team. Not sure where you fit in? We hail from many disciplines, including: Operations Research, Machine Learning, Statistics, Econometrics, Industrial Engineering, and Applied Mathematics. If your expertise lies in data mining, analytical consultation and science modeling, this could be the perfect role for you.

Your Role:

  • 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 as well as 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 (statistics, operations research, etc.) to multiple Walt Disney Company business units including Walt Disney Parks & Resorts, Disney Cruise Line, Media Networks (e.g., ABC, ESPN), Studio Entertainment (e.g., The Walt Disney Studios, Disney Theatrical Group), and Disney Consumer Products and Interactive Media

What We’re Looking For:

  • Possess a Master’s degree in Statistics, Operations Research, Industrial Engineering, Mathematics, Econometrics or related field
  • Minimum three years related/relevant experience
  • Ability to work with little guidance on science methodologies and modeling approaches, based on sound business acumen, across multiple lines of business or functional areas
  • Ability to provide peer leadership to junior colleagues, and to direct the design and development of advanced analytical data mining, forecasting, estimation, and/or optimization models
  • Ability to provide project management leadership and technical guidance for Decision Science work streams and activities
  • Ability to work with project teams (clients, partners, contributors) to ensure successful implementation of science solutions to include all phases of the project: requirements gathering, design, implementation, quality assurance, and maintenance
  • Must exhibit competence in at least one of the following analytics/science fields, and in one of the following computing languages:

Statistics (2 or more areas):

  • Generalized linear models
  • Nonparametric regression
  • Bayesian statistics
  • Time series (State space models, ARIMA, …)
  • Mixture models
  • Structural equation models

Optimization (at least one):

  • Mixed-integer
  • Non-linear
  • Stochastic
  • Stochastic Models and Discrete-Event Simulation
  • Decision Analysis or Multiple Criteria Decision Making

Econometrics (2 or more areas):

  • Panel data
  • Limited dependent variables
  • Generalized method of moments
  • Simultaneous equations models
  • Instrumental variables

Machine learning (2 or more areas):

  • CART
  • Random forests
  • Neural networks
  • Boosting
  • Support vector machines
  • Graphical models
  • Clustering
  • Reinforcement learning

Computing & programming languages (at least one):

  • Scientific computing (MATLAB, Julia, etc.)
  • Statistical (SAS, R, etc.)
  • General (Java, Python, C, C++, etc.)

How To Stand Out:

  • Proven knowledge of revenue management context, including demand forecasting, resource allocation, and pricing
  • Possess a PhD in Statistics, Operations Research, Industrial Engineering, Mathematics, Machine Learning, Econometrics or related field
Interested in this position?
Job Location
Lake Buena Vista, FL
Additional Job Details
Employment Type:
Full Time
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