Amazon Pharmacy
Pharmacy
Manager,AppliedScience
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optimal for Manager candidates.
“Manager, Applied Science at Amazon Pharmacy. Skills: Machine Learning, Supply Chain, Operations Research, Optimization. Lead engineers building ML systems. Hire engineers”
What You'll Achieve.
Ensure medication in stock; Ensure medication at right facility; Ensure medication at right time
Industry & Context.
Root cause analysis; Troubleshooting; Data-driven decision making
What They're Looking For.
Must Have
Master's degree in quantitative field, 5+ years management experience
Nice to Have
PhD in quantitative field, 5+ years building ML models, Experience building complex software systems, Experience building ML models for business application
What You'll Do.
Lead engineers building ML systems
Define technical roadmap
Identify modeling opportunities
Set bar for scientific rigor
Translate quantitative methods
Manage team's work portfolio
Balance production improvements
Design demand forecasting systems
Develop optimization models
Design placement algorithms
Apply operations research techniques
Develop capacity planning models
Translate scientific methods
Design experimentation frameworks
Build backtesting infrastructure
Establish performance metrics
How You'll Work.
Team & Collaboration
Peer SDMs; Product managers; US-based teams; Technical reviews; Science reviews
Process & Methodology
Roadmap planning
Full Job Description
Join Amazon Pharmacy as the founding engineering leader for our Supply Chain technology team in Bangalore. You will build and lead a team of engineers responsible for the systems that determine what medications to buy, where to place inventory, and how to plan capacity across Amazon Pharmacy's fulfillment network. This is a greenfield opportunity to architect ML-driven supply chain systems from the ground up, leveraging Amazon's cloud-native infrastructure, proven supply chain optimization patterns, and operations research best practices at Amazon scale. You will own the full supply chain stack for Amazon Pharmacy: demand forecasting, procurement optimization, inventory placement, resource planning, and Sales & Operations Planning (S&OP). Your systems will directly determine whether a patient's medication is in stock, at the right facility, at the right time. The stakes are high: pharmacy supply chains operate under regulatory constraints, drug expiry windows, and prescription-driven demand signals that make this one of the most technically interesting supply chain problems at Amazon. We are building an AI-native engineering organization. You will operate with a flat structure, leading senior ICs directly, and leveraging AI-augmented development workflows (code generation, automated testing, ML-driven monitoring) to move fast with a lean team. If you are energized by building ML-intensive systems, leading from the front technically, and setting the culture for a high-autonomy engineering team, this is your role. Key job responsibilities A. Engineering Leadership & Team Building • Lead a team of engineers building ML-driven and optimization-based supply chain systems • Hire engineers who can operate at the intersection of software engineering and quantitative methods • Define the technical and science roadmap: identify high-impact modeling opportunities across demand forecasting, procurement, placement, and planning • Set the bar for scientific rigor: reproducibility
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