Amazon Science gives you insight into the company’s approach to customer focused scientific innovation. Amazon fundamentally believes that scientific innovation is essential to being the most customer-centric company in the world. It’s the company’s ability to have an impact at scale that allows us to attract some of the brightest minds in artificial intelligence and related fields. Our scientists continue to publish, teach, and engage with the academic community, in addition to utilizing our working backwards method to enrich the way we live and work.

Please visit https://www.amazon.science for more information.

Are you an expert in Neural Network, Graph Models and Probabilistic Risk Modeling? Are you interested in building AI-driven solutions on complex business problems that have significant global benefit. The Brand Protection ML team designs and builds high performance AI systems using machine learning that identify fraudulent and abusive entities to protect customers, brands, selling partners and the Amazon store worldwide from counterfeit and other forms of IP infringements.

We are looking for a highly talented scientist to help build of our vision for Brand Protection. As an applied scientist on the team, You will play a key role in designing, developing, and deploying advanced graph-based models that detect hidden relationships, anomalous behaviors, and emerging risks in large-scale, complex data environments. You will work backwards from data insights and customer feedback to build the right machine learning solutions, and resourceful in finding innovative solutions to unsolved problems. You will work closely will product team and engineering partners to launch the solution into production and owning the end-to-end solution.

An ideal candidate should have hands-on experience developing end-to-end Machine Learning solutions at industrial setting, specially in graph-based algorithms (e.g., Graph Neural Networks, representation learning, community detection, link prediction) for fraud and risk detection, from conception to launch in a rapidly evolving environment. Amazon’s growth requires leaders who move fast, have an entrepreneurial spirit to create new solutions, have an unrelenting tenacity to get things done, and are capable of breaking down and solving complex problems.

Major responsibilities:
- Understand business challenges by analyzing data and customer feedback
- Collaborate with tech and product teams on building ML strategies, experimentation, implementation and continuous improvement post-launch
- Analyze and extract relevant information from large amounts of both structured and unstructured data to design strategies to solve business problems.
- Develop and apply graph-based algorithms (e.g., Graph Neural Networks, representation learning, community detection, link prediction) for fraud and risk detection.
- Design scalable data pipelines to construct, enrich, and maintain large-scale knowledge graphs from heterogeneous data sources.
- Present research and analytics insights with stakeholders and partners to advance organizational science knowledge and decision making
- Research and implement novel AI solutions and publish research papers internally (and externally where appropriate)

About the team
Here at Selling Partner Services, we embrace our differences. We are committed to furthering our culture of inclusion. We have 14 employee-led affinity groups, reaching 10,000+ employees in chapters globally. We have innovative benefit offerings, and we host annual and ongoing learning experiences, including our DEI Ambassador Program. Amazon’s culture of inclusion is reinforced within our 16 Leadership Principles, which remind team members to seek diverse perspectives, learn and be curious, and earn trust.

Applied Scientist, Brand Protection ML