Decision Scientist P2

• 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.
• Theteam 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.

• Achieve business goals and objectivesResearch and develop decision science models and act as a consultant to all business units
• Pursue innovationConduct research on analytical techniques and translate that research into usable and sustainable solutions for users
• Put your skills to the testPerform data collection and data mining and build state-of-the-art decision science algorithms tools and systems
• Drive valueModel and analyze revenue management and pricing related issues using various mathematical statistical and simulation techniques
• Tell the storyPresent science results to business partners and clients
• Support a global and enterprise-wide missionIdentify and apply best practices in the field of advanced analytics for multiple businesses such as theme parks and resorts

• Bayesian statistics
• Generalized linear models
• Mixture models
• Nonparametric regression
• Structural equation models
• Time series (state space models ARIMA etc.)

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

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

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

• Proven knowledge of revenue management context including demand forecasting resource allocation and pricing
• Proven knowledge of viewership estimation audience and demo profiles and impressions monetization in the linear media advertising context

• Masters or Ph.D. degree in Statistics Operations Research Industrial Engineering Mathematics Machine Learning Econometrics or related field
• Creates and supports mathematical models for forecasting simulation estimation or optimization based on theoretical principles and methodological research. Performs data preparation exploration and validation. Supports calibration testing validation and sustainment of models.
• Has theoretical knowledge underlying methods of applicable technical discipline (e.g. statistics optimization machine learning or econometrics) and applies theoretical understanding to identify the right model or approach.
• Knows detailed business context for scope of assigned work within a given line of business (e.g. cruise line ABC) and within a given business domain (e.g. pricing finance marketing supply chain) and applies technical discipline to assigned line of business & business domain to develop algorithms via tools such as Python R Tableau Gurobi.
• Impacts the success of a smaller analytical project or a component of a large project involving new models. Collaborates effectively to ensure own work is well-integrated. May guide less experienced colleagues.
• Education: Masters or Ph.D. in technical discipline (Statistics Operations Research Industrial Engineering Mathematics Machine Learning Econometrics or related field) or equivalent experience

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