Senior Applied Scientist, AWS Marketplace Discovery

About the team

The AWS Marketplace & Partner Services Science team is at the forefront of developing and deploying AI/ML systems that serve multiple critical stakeholders:

• AWS Customers: Through the AWS Marketplace, we support Discovery tools that streamline cloud adoption and innovation.
• AWS Partners: Via Partner Central, we offer advanced tools and insights to enhance collaboration and drive mutual growth.
• Internal AWS Sellers: We equip our sales force with data-driven recommendations to better serve our customers and partners.

Key job responsibilities

• Lead the research, design, and development of advanced AI/ML systems for information retrieval and personalized recommendation systems
• Identify and evaluate emerging scientific techniques and technologies, translating research into practical, scalable solutions
• Drive evaluation and hypothesis testing to continuously improve performance and relevance of search and recommendation systems
• Collaborate with cross-functional teams, such as Product and Engineering leaders, to translate scientific innovations into customer value
• Mentor Scientists and influence scientific approach across the organization
Qualifications
• Basic Qualifications: 3+ years of building machine learning models or developing algorithms for business application experience, experience programming in Java, C++, Python or related language, experience working on recommender systems or personalization within search, e-commerce, shopping, advertising or other related fields
• Preferred Qualifications: PhD in Science, Technology, Engineering, or Mathematics (STEM), or Master's degree and 5+ years of working with or evaluating AI systems experience, experience conveying complex technical concepts to both technical and business audiences, experience providing and effectively communicating strategic and tactical recommendations based on data, 6+ years of building large-scale machine-learning infrastructure for online recommendation, ads ranking, personalization or search experience