Job description
Amazon is investing heavily in building a world-class advertising business, and the EDGE Science team is at the forefront of developing innovative, scalable advertising solutions that drive business impact across entertainment, device, and grocery advertising experiences.
We build publisher-agnostic approaches that optimize advertising across Amazon's entertainment devices and physical stores, delivering sustainable revenue growth while maintaining excellence in customer experience.
Our team specializes in developing advanced capabilities that both enhance customer experience and accelerate business growth across Amazon's diverse ecosystem.
The EDGE Science team builds innovative solutions for Amazon entertainment and devices (Prime Video, Fire TV, Fire tablet, Alexa, etc.) and physical store environments, leveraging data and machine learning to deliver personalized and relevant ads to customers.
We focus on driving business impact through increased engagement, conversion, and revenue while fostering a culture of innovation, experimentation, and continuous learning.
We are seeking a passionate Applied Science Manager to lead a cross-functional team of Applied and Data Scientists, and collaborate with technical leaders and non-technical stakeholders.
You will drive the science strategy and roadmap to invent and build scalable solutions for context-aware advertising across entertainment devices and grocery experiences.
Key job responsibilities
- Define and execute the strategic vision for advertising science across entertainment devices and grocery experiences, establishing a roadmap that balances short-term business impact with long-term scientific innovation.
- Independently manage and grow a high-performing team of scientists and engineers, providing technical guidance, career development, and fostering a culture of experimentation and continuous learning.
- Drive the development of novel advertising solutions that work seamlessly across Amazon's entertainment device ecosystem and physical store environments, focusing on publisher-agnostic approaches.
- Lead the development of sophisticated machine learning models for personalized advertising, leveraging multi-modal data from devices, customer behavior, and contextual signals to optimize ad relevance and performance.
- Rapidly design, prototype, and test hypotheses in high-ambiguity environments, ensuring all solutions drive measurable business impact through increased engagement, conversion, and revenue.
- Foster cross-team collaboration with engineering, product, and business teams to execute complex projects and drive alignment across organizations for science, engineering, and product strategy.
- Maintain robust measurement and monitoring systems for models and business metrics, ensuring sustainable revenue growth and avoiding short-sighted optimizations.
- Perform hands-on data analysis, build machine learning models, run A/B tests, and communicate impact to senior management while staying current with relevant scientific publications.
- Hire and develop top talent, providing technical and career development guidance to scientists and engineers within and across the organization.
About the team
The EDGE Science team operates with a mission to build innovative advertising solutions that work across Amazon's entertainment devices and physical stores.
We follow key tenets including customer and advertiser focus, iterative delivery, balanced pragmatism, continuous measurement, sustainable revenue growth, active collaboration, and swift action with smart risk management.
Our team values real-world impact over academic novelty and employs the simplest effective solutions while investing in deeper science where needed for long-term ROI.
BASIC QUALIFICATIONS
- 4+ years of applied research experience
- 3+ years of scientists or machine learning engineers management experience
- 3+ years of building machine learning models for business application experience
- PhD, or Master's degree and 6+ years of applied research experience
- Knowledge of ML, NLP, Information Retrieval and Analytics
- Experience programming in Java, C++, Python or related language
- Experience with large-scale distributed systems and real-time ML applications
PREFERRED QUALIFICATIONS
- Experience building complex software systems, especially involving deep learning, machine learning and computer vision, that have been successfully delivered to customers
- Experience with advertising technology, recommendation systems, or personalization at scale
- Knowledge of multi-modal ML approaches combining text, image, audio, and behavioral signals
- Experience with A/B testing, causal inference, and experimentation in production environments
- Understanding of devices, streaming media, or retail technology
- Experience with privacy-preserving ML techniques and federated learning approaches
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.
Our inclusive culture empowers Amazonians to deliver the best results for our customers.
Required Skill Profession
Life Scientists
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