The Director of Economic Value for Amazon Devices and Services (Amazon Devices) is charged with building scientific products and processes to measure and drive the long-term flywheel value of Amazon Devices for product line (PL) resource allocation, profitability prediction in product development, and merchandising and monetization optimization. This is a critical role whose vision and leadership will have broad impact on business priorities and decisions in Amazon Devices.
The Amazon Devices business builds and promotes Amazon first-party consumer electronics products to delight customers. The broad product portfolio includes Kindle, FireTV, Fire Tablet, Echo, Ring, and eero devices that meet diverse customer needs including entertainment, Alexa audio assistant, home security, and wifi access. The portfolio is dynamic with new product launches, and complementary with increased connection and utility from multiple devices and supplemental subscription services. Together, these durable products and services drive a flywheel business where long-term customer benefits yield greater device engagement, demand for related devices, and broader purchasing behavior with Amazon.
The Devices Economic Value team is the Amazon team that leads scientific measurement of customer behavioral responses to devices, and the flywheel value to Amazon. The team owns three areas: 1) long-term value methods to scientifically measure and forecast lifetime value lift for devices customers, and the data systems to report and embed results in financial processes; (ii) Customer engagement value: methods and systems to measure and report revenue and profitability lift from increased device engagement, for use in monetization and merchandising processes; and (iii) New product profitability: predicting lifetime value of future products for use in new product development decision making. The team achieves impact through methods innovation, analytic studies, and integration with business-facing tools.
The Devices Economic Value team needs a leader to build on existing successes to scale and advance the team and team outputs to address the increasing complexity of the space. The increased complementary of products and the expanding product offering affect the capacity to measuring long-term effects reliably, accurately, and actionably. New opportunities could include experimentation, recommendation systems for merchandising, and product feature optimization for long-term value creation. The space needs a visionary leader interested in tackling these strategic science problems, and building products to embed insights in business decisions and processes.
This role will work closely with Amazon Devices executive leadership in finance and product to help shape our organizational investment strategies through science roadmaps. In addition, this is a strategic cross-org role that will collaborate in Amazon-wide initiatives to advance and standardize economic measurement of durable goods. The role is high visibility and high impact. The ideal candidate must have excellent communication skills (verbal and written), and be passionate about advancing science for business and customer impact.
Amazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status. For individuals with disabilities who would like to request an accommodation, please visit https://www.amazon.jobs/en/disability/us
• Graduate degree in a technical or management field
• 6+ years of professional experience in analytics and applied economics
• Demonstrated experience leading analytic and science teams, with a record of developing and executing an analytic vision to solve business-relevant problems
• Track record in hiring top talent, and passion for developing talent
• Leadership experience in highly cross-functional and complex work environments
• Written and verbal communications skills to convey complicated process and systems to business partners and senior leadership.
• PhD in Economics, Statistics, Psychology, Management Science or another quantitative field.
• Applicants with considerably more and broader, experience, are also strongly encouraged
• Experience with causal machine learning in performant applications
• Experience with long-term behavioral modeling and valuation for business applications