Amazon.com Services LLC
Machine Learning Science, Applied Science, operations
Sr.Manager,AppliedScience,SupplyChainOptimizationTechnologies
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“Sr. Manager, Applied Science, Supply Chain Optimization Technologies at Amazon.com Services LLC. Skills: Machine Learning, Reinforcement Learning, Supply Chain Optimization. Lead technical innovation in RL. Build and develop high-performing team”
What You'll Achieve.
Build world's most efficient supply chain; Run world's most efficient supply chain; Continuously improve supply chain
Industry & Context.
Solving toughest real-world problems
What They're Looking For.
Must Have
Ph.D. in Computer Science, Ph.D. in Applied Mathematics, Ph.D. in Statistics, Hands-on ML model building, Hands-on optimization model building, 3+ years managing science team, Expertise in modern Python, Large-scale data processing
Nice to Have
Manage business improvement quantification, Manage analytics improvement quantification, Manage optimization improvement quantification, Manage statistical modeling improvement, Manage senior scientists, Develop junior members, Peer-reviewed scientific contributions, Familiarity with inventory planning, Forecasting knowledge, Planning knowledge, Optimization knowledge, Logistics knowledge, Verbal communication skills, Written communication skills, Presentation skills, Convey mathematical concepts to non-experts, Work effectively in cross-functional team
What You'll Do.
Lead technical innovation in RL
Build and develop high-performing team
Create balanced culture
Bridge technical possibilities with business requirements
Provide strategic judgment
Evaluate technology feasibility
Manage implementation risk
Drive cross-functional collaboration
Interface with product teams
Interface with leadership
Interface with partner organizations
Translate business needs into technical solutions
How You'll Work.
Team & Collaboration
Cross-functional collaboration; Interface with product teams; Interface with partner organizations
Communication Scope
Verbal communication; Written communication; Presentation skills
Full Job Description
Are you seeking an environment where you can drive innovation? Do you want to be at the forefront of solving the toughest real-world supply chain problems? Do you want to play a key role in the future of Amazon's Stores business? Come and join us! Supply Chain Optimization Technologies (SCOT) owns Amazon's global inventory planning systems. We decide what, when, where, and how much we should buy to meet Amazon's business goals and to make our customers happy. We decide how to place and move inventory within Amazon's fulfillment network. We do this for hundreds of millions of items and hundreds of product lines worth billions of dollars worldwide. Check our website if you are curious to learn more about the breadth of problems we tackle: https://www.amazon.science/tag/supply-chain-optimization-technologies We are seeking a Sr. Manager of Applied Science with expertise in Statistical Machine Learning and/or Reinforcement Learning to drive research, development, and deployment of AI technology that empowers SCOT to build, run, and continuously improve the world's most efficient supply chain. To achieve this goal, we accelerate ML / RL software adoption through our partnerships and infrastructure. In this role, you will manage a team of scientists tasked researching the next generation of solutions to power buying, placement, and fulfillment decisions, while translating customer needs into reusable software infrastructure that accelerates adoption and deployment. Key job responsibilities - Lead technical innovation in reinforcement learning applications for complex supply chain environments, solving unique challenges and ensuring practical implementation in real-world deployments. - Build and develop a high-performing team by fostering collaboration, mentoring top talent, and creating a balanced culture of technical excellence. - Bridge technical possibilities with business requirements by providing strategic judgment, evaluating technology feasibility, and managing imp
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