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Amazon
The AWS Supply Chain organization is looking for a Sr. Manager of Applied Science to lead science and data teams working on innovative AI-powered supply chain solutions. As part of the AWS Solutions organization, we have a vision to provide business applications, leveraging Amazon’s unique experience and expertise, that are used by millions of companies worldwide to manage day-to-day operations. We will accomplish this by accelerating our customers’ businesses through delivery of intuitive and differentiated technology solutions that solve enduring business challenges. We blend vision with curiosity and Amazon’s real-world experience to build opinionated, turnkey solutions. Where customers prefer to buy over build, we become their trusted partner with solutions that are no-brainers to buy and easy to use.
Are you excited about developing state-of-the-art GenAI/Agentic AI based solutions for enterprise applications? As a Sr. Manager of Applied Scientist at AWS Supply Chain, you will bring AI advancements to customer facing enterprise applications. In this role, you will drive the technical vision and strategy for your team while fostering a culture of innovation and scientific excellence. You will be leading a fast-paced, cross-disciplinary team of researchers who are leaders in the field. You will take on challenging problems, distill real requirements, and then deliver solutions that either leverage existing academic and industrial research, or utilize your own out-of-the-box pragmatic thinking. In addition to coming up with novel solutions and prototypes, you may even need to deliver these to production in customer facing products.
Key job responsibilities
Building and mentoring teams of Applied Scientists, ML Engineers, and Data Scientists.
Setting technical direction and research strategy aligned with business goals.
Driving innovation in Supply Chains systems using AI/ML models and AI Agents.
Collaborating with cross-functional teams to translate research into production.
Managing project portfolios and resource allocation.