How can we create a rich, data-driven shopping experience on Amazon? How do we build data models that helps us innovate different ways to enhance customer experience? How do we combine the world's greatest online shopping dataset with Amazon's computing power to create models that deeply understand our customers?
Recommendations at Amazon is a way to help customers discover products. Our team's stated mission is to "grow each customer’s relationship with Amazon by leveraging our deep understanding of them to provide relevant and timely product, program, and content recommendations". We strive to better understand how customers shop on Amazon (and elsewhere) and build recommendations models to streamline customers' shopping experience by showing the right products at the right time. Understanding the complexities of customers' shopping needs and helping them explore the depth and breadth of Amazon's catalog is a challenge we take on every day.
Using Amazon’s large-scale computing resources you will ask research questions about customer behavior, build models to generate recommendations, and run these models directly on the retail website. You will participate in the Amazon ML community and mentor Applied Scientists and software development engineers with a strong interest in and knowledge of ML. Your work will directly benefit customers and the retail business and you will measure the impact using scientific tools. We are looking for passionate, hard-working, and talented Applied scientist who have experience building mission critical, high volume applications that customers love. You will have an enormous opportunity to make a large impact on the design, architecture, and implementation of cutting edge products used every day, by people you know.
Key job responsibilities
- Scaling state of the art techniques to Amazon-scale
- Working independently and collaborating with SDEs to deploy models to production
- Developing long-term roadmaps for the team's scientific agenda
- Designing experiments to measure business impact of the team's efforts
- Mentoring scientists in the department
- Contributing back to the machine learning science community
- PhD degree with 4 years of applied research experience or a Masters degree and 6+ years of experience of applied research experience
- 3+ years of experience in building machine learning models for business application
- Experience programming in Java, C++, Python or related language
- Significant peer reviewed scientific contributions in relevant field.
- Extensive experience applying theoretical models in an applied environment.
- Expertise on a broad set of ML approaches and techniques, ranging from Artificial Neural Networks to Bayesian Non-Parametric methods.
- Strong Experience in Structured Prediction and Dimensionality Reduction.
- Expert in more than one more major programming languages (C++, Java, or similar) and at least one scripting language (Python, R, or similar).
- Proven track record of production achievements in language, search and personalization.
- Strong fundamentals in problem solving, algorithm design and complexity analysis.
- Strong personal interest in learning, researching, and creating new technologies with high commercial impact.
- Experience with defining organizational research and development practices in an industry setting.
- Proven track in leading, mentoring and growing teams of scientists (teams of five or more scientists).
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.