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# Decision Scientist

- **Company:** The Walt Disney Company
- **Location:** Lake Buena Vista, FL, United States
- **Experience:** Experienced
- **Salary:** $111,900.0 - $150,000.0
- **Contract:** Permanent contract
- **Skills:** Artificial Neural Networks, Cluster Analysis, Discrete Event Simulation, Game Theory, Generalized Linear Model, Python (Programming Language), Machine Learning, Support Vector Machine, Reinforcement Learning, Random Forest, Software Coding, Programming Languages
- **Published:** October 5, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=fec16b35dee60e6a

## About the Role

* Minimum of 3 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 programming language.

Competence in at least one quantitative field, as indicated by the completion of advanced coursework and original research., * Experience using advanced analytics to shape high-impact strategic or enterprise-level decisions, ideally in complex or fast-moving business environments.

 * Expertise in decision theory, system dynamics, industrial organization, or other approaches for understanding and influencing decisions in complex systems.
 * Ability to translate sophisticated analytical methods into clear, actionable insights for leaders and non-technical partners.
 * 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 Statistics, Applied Mathematics, Operations Research, Econometrics, Economics, Machine Learning, or comparable field of study, and/or equivalent work experience

## Description

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. As an analytical Center of Excellence, we are responsible for developing and delivering data science courses to business professionals across the enterprise, including individual contributors and executives. As a Decision Scientist - Course Developer/Instructor, you will play a pivotal role in designing and teaching these courses. In addition, you will have opportunities to develop innovative decision science solutions that support critical projects for internal clients. This role will work under the direction of the Senior Manager, Decision Science., * Drive value through analytics - Research, develop, and implement decision science frameworks as a consultant to business units across The Walt Disney Company.

 * Pursue innovation - Conduct research on analytical techniques and translate that research into practical solutions for users and clients.
 * 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., * Bayesian statistics
 * Generalized linear models
 * Design of Experiments
 * 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/Economics (two or more topics):
 * Difference in differences
 * Instrumental variables
 * Panel data
 * Regression discontinuity design
 * Simultaneous equations models
 * Dynamic stochastic general equilibrium modeling
 * Game Theory
 * Machine learning (two or more topics):
 * Boosting
 * CART
 * Clustering
 * Graphical models
 * Neural networks
 * Random forests
 * Reinforcement learning
 * Support vector machines