Disney Decision Science and Integration (DDSI) is an analytical Center of Excellence that provides internal consulting services for clients across The Walt Disney Company including Disney Parks, Experiences and Products (DPEP), Disney Entertainment (e.
g.
, ABC, The Walt Disney Studios, Disney Theatrical, etc.
), ESPN (ESPN Networks, ESPN+), and Corporate Finance.
In DDSI, we sit 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.
We are also responsible for crafting and teaching courses in data science to other businesses across the Company.
This training drives value by "upskilling" individuals in data visualization, process automation, causal inference, probability & uncertainty, modern forecasting & prediction, mathematical optimization, and other analytical areas.
As a Decision Scientist – Course Developer/Instructor, you will play a pivotal role in designing and delivering these courses in addition to other decision science responsibilities to provide analytical support for internal clients.
This role will work under the direction of the Manager, Decision Science – Upskilling.
What You Will Do
Responsibilities as a Decision Scientist Course Developer/Instructor
Develop courses on analytical topics such as probability and uncertainty in business decision making, mathematical optimization for business processes, coding for automation and data analytics, machine learning for business forecasting and prediction, data visualization for business intelligence, among others.
Teach courses on data science to business professionals and consult on how to best apply methods taught in the courses to their daily work.
Additional responsibilities as a Decision Scientist:
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 balanced solutions for users.
Put your skills to the test—Perform data collection and data mining, and build innovative 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 lines of business.
Basic Qualifications:
Minimum of 1 year of related work experience.
Ability to teach concepts on technical subject matter to non-experts in a clear and memorable way.
Ability to craft technical slides, animations, and scripts to be used in teaching live or remote audiences.
Excellent written and spoken English.
Proficient at writing code in at least one programming language like R, Python, Julia, or other coding language.
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):
Difference in differences
Instrumental variables
Panel data
Regression discontinuity design
Simultaneous equations models
Machine learning (two or more topics):
Boosting
CART
Clustering
Graphical models
Neural networks
Random forests
Reinforcement learning
Support vector machines
Preferred Qualifications:
Proven knowledge of revenue management context, including demand forecasting, resource allocation, and pricing.
Experience developing data-science training for business professionals.
Required Education
Master’s degree in Advanced Mathematics, Statistics, Data Science, or comparable field of study, and/or equivalent work experience
Preferred Education
Ph.
D.
degree in advanced Mathematics, Statistics, Data Science, or comparable field of study, and/or equivalent work experience
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