Applied Machine Learning Scientist

Data Scientist/Machine Learning The successful candidate will be responsible for developing an advanced machine learning model to forecast domestic consumer demand and spending for Premium Video on Demand (PVOD) and Premium Electronic Sell-Through (PEST) at the individual film title level. This role will involve improving current box office-based methods by incorporating diverse features such as marketing, film quality, competition, and pricing. Key Responsibilities • Develop and implement a machine learning model to forecast consumer demand and spending for PVOD and PEST. • Incorporate diverse features such as marketing, film quality, competition, and pricing into the model. • Support early-stage and post-theatrical forecasting modes. • Ensure model explainability for non-technical stakeholders. • Provide guidance for integration of the model into weekly workflows. • Utilize historical data on theatrical performance, film attributes, marketing, pricing, and competitive context. • Deliver a predictive model, explainability package, accuracy assessment, and implementation recommendations within a four-week timeline. Requirements Required Qualifications: • Proven experience in machine learning model development and implementation. • Strong understanding of forecasting methods and techniques. • Proficiency in programming languages such as Python or R. • Experience with data analysis and feature engineering. • Ability to work with historical data and incorporate diverse features into models. • Excellent communication skills to explain complex models to non-technical stakeholders. • Strong problem-solving skills and attention to detail. Preferred Qualifications: • Experience in the entertainment industry or with PVOD and PEST forecasting. • Knowledge of marketing, film quality, competition, and pricing factors. • Familiarity with early-stage and post-theatrical forecasting modes. Compensation • $60.00 to $70.00/hr. (W2) Req# PPCJP00000487