Applied Scientist, Marketing Science - Prime Video

Prime Video & Amazon MGM Studios; New York (NY); On-site; USD 157,000 - 213,000; Full time

Benefits offered by this job

Health insurance

401(k) matching

Paid time off

Parental leave

Job summary

Amazon.com Services LLC in New York, NY is seeking an Applied Scientist for Prime Video to own marketing measurement models and optimize investment decisions. You will develop sequential decision-making frameworks and forecasting systems that adapt as customer behavior evolves across campaigns and markets.

You will collaborate with business and finance teams to translate questions into well-posed statistical problems, quantify uncertainty, and communicate insights clearly to stakeholders.

Qualifications

• Master’s or higher in a technical field relevant to machine learning.
• Experience building ML models or algorithms for business applications.
• Proficiency in programming languages such as Java/C++/Python.

Responsibilities

• Build sequential decision-making frameworks (e.g., MDPs, bandits) to optimize marketing resource allocation.
• Create predictive models to forecast marketing efficiency and budget allocation.
• Design geo-level hold-out experiments to validate model predictions.
• Automate and scale modeling infrastructure for broader coverage.
• Collaborate with business and finance to translate questions into statistical problems.
• Quantify uncertainty and communicate results to non-technical stakeholders.

Skills

Java/C++/Python

ML Algorithms

Education

Master’s degree or above in Engineering/CS/ML/OR/Statistics

PhD in Engineering/CS/ML/OR/Statistics

Job description

Amazon.com Services LLC in New York, NY is seeking an Applied Scientist for Prime Video to own marketing measurement models and optimize investment decisions. You will develop sequential decision-making frameworks and forecasting systems that adapt as customer behavior evolves across campaigns and markets.

You will collaborate with business and finance teams to translate questions into well-posed statistical problems, quantify uncertainty, and communicate insights clearly to stakeholders.