Interested in helping the next generation of the customer personalization and experimentation science that drives the Prime membership program? Join our team of highly skilled Scientists and Engineers developing algorithms to adaptively generate personalized image/text/video, rank across different cross-benefit items and Prime offers, and drive membership profitability with Amazon Prime.
There are numerous scientific and technical challenges you will get to tackle in this role, such as adaptive experimentation, use of Gen AI to understand deep customer insights, state of the art recommender systems to recommend items from huge catalog of cross-benefit items and offers, and create personalized content that can serve customer needs across different Amazon and non-Amazon surfaces. Finally, these experiences should adapt using multi-step optimization and reinforcement learning of the customer journey across multiple touchpoints. We employ techniques from GenAI, transforms, deep learning, RL within the team and are looking for the science manager to raise the bar on science and operations within the team.
As the central science team within Prime, our expertise gets routinely called upon to weigh in on a variety of topics. We also emphasize the need and value of scientific research and have developed a strong publication and patent record (internally/externally) which you will be a part of.
You will also utilize and be exposed to the latest in ML technologies and infrastructure: AWS technologies (EMR/Spark, Redshift, Sagemaker, DynamoDB, S3, ...), various ML algorithms and techniques (Random Forests, Neural Networks, supervised/unsupervised/semi-supervised/reinforcement learning, LLM's), and statistical modeling techniques.
Major responsibilities
- Supervise the development of AI and machine learning models and supporting infrastructure at TB scale, in coordination with software engineering teams.
- Leverage GenAI, transformers, deep learning and Reinforcement Learning for Experimentation, Personalization, and Generation Systems.
- Develop offline policy estimation tools and integrate with reporting systems.
- Collaborate with Economists, scholars, and other AI teams in related areas across Amazon to build strong interoperability of solutions.
- Be closely integrated with Amazon and external science communities through publications, talks, reviews.
- Establish scalable, efficient, automated processes for large scale data analyses, model development, model validation and model implementation.
- Work closely with the business to understand their problem space, identify the opportunities and formulate the problems.
- Design, develop and evaluate highly innovative models and statistical approaches to understand and predict customer behavior and to solve business problems.
- Hire and develop the best in class scientists to raise the bar for science within Prime and Amazon.
- Establish a long-term vision for the team, inform vision for the org, establish short term roadmap, OP1 and monthly Sprints and roadmaps.
- Report on performance of AI/ML systems in QSR's, and reviews with leadership, and represent the team in leadership and cross-team reviews.
