Prime Video is an industry leading, high-growth business and a critical driver of Amazon Prime subscriptions, which contribute to customer loyalty and lifetime value. Prime Video is used daily by a massive audience on Amazon's websites and through a variety of devices including the Kindle Fire, game consoles, smart TVs and Blu-ray players. Prime Video is a digital video streaming and download service that offers Amazon customers the ability to rent, purchase or subscribe to a huge catalog of videos. Movies range from new releases to classic favorites, and Prime Video offers major television episodes, entire seasons, or even day after air TV.
The Video Content Research (VCR) team uses machine learning, econometrics, and data science to optimize Amazon’s streaming-video catalogue, driving customer engagement and Prime member acquisition. We generate insights to guide Amazon’s digital-video strategy, and we provide direct support to the content-acquisition process. We use detailed customer behavioral data (e.g. streaming history) and detailed information about content (e.g. IMDb-sourced characteristics) to predict and understand what customers like to watch.
We are looking for a senior economist to help measure the impact of engagement with Prime Video content and integrate it into our content valuation framework.
This position is open to the following locations: Seattle, Los Angeles
Key job responsibilities
Lead the development of a consistent, integrated framework for how Prime Video values each title given upstream and downstream model constraints
Interact with senior leaders with Prime Video, both technical and non-technical, to understand their primary use cases
Independently write technical and business documents to communicate ideas and proposals to various audiences
Incorporate new data sources and creative methodology innovations to improve model performance
Mentor junior teammates to improve their understanding and application of science to causal and structural economic problems
- PhD in Economics or closely related field
Applicants with considerably more experience, including mid-career, are also strongly encouraged
Strong background in statistics methodology, applications to business problems, and/or big data
Ability to work in a fast-paced business environment
Strong research track record
Effective verbal and written communications skills
Strong causal estimation based on observational data
Strong technical communication to non-technical audience
Experience in optimization and microeconomic modeling
Experience working with very large real-world data sets and building scalable models from big data
Expertise in SQL and a programmatic scripting language for analysis (e.g. Python/R)
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