Decision Scientist P2

Role: Sr. Decision Scientist

Industry: Entertainment

Location: Remote, EST Hours

Duration: 12+ months

Rate Range: $80-$88/hr

Work Requirements: US Citizen, GC Holders or Authorized to Work in US

Description:

• 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 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
• 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

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.)

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.)

How to Stand Out:

• 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

Required

Education:

• Master's 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…