Applied Scientist - Large-Scale Optimization & Forecasting

Amazon Science; New York (NY); On-site; USD 172,400 - 223,400; Full time

Benefits offered by this job

Health insurance

401(k) matching

Paid time off

Parental leave

Mental health support

Job summary

Amazon Science in New York is seeking a senior scientist to design and deploy large-scale optimization and forecasting models that plan inventory and flow across our fulfillment network. You will shape the mathematical architecture of the planning system and push the frontier of solver technology for fast, reliable results.

You will work with cross-functional partners to take ideas from whiteboard to production, owning them end-to-end once live, and contribute to long-term scientific vision in

Qualifications

• 3+ years of building models for business applications.
• PhD or MS with 4+ years in CS/CE/ML or related field.
• Experience in patents or publications at top-tier conferences/journals.
• Experience programming in Java, C++, Python or related language.

Responsibilities

• Build state-of-the-art, robust, scalable stochastic optimization and probabilistic forecasting algorithms for planning under uncertainty across Amazon's supply chain.
• Shape how large-scale planning problems are formulated, decomposed, and solved for performance and reliability at scale.
• Engineer algorithms as production-grade, cloud-native software from prototype to deployment.
• Think ahead to architect long-term scientific solutions while shipping incremental improvements.
• Prototype fast, run pilots, and iterate with operational feedback to production.

Skills

Large-scale optimization

Forecasting models

Production-grade software

Cloud-native software

Education

PhD or MS in CS/CE/ML or related field

Tools

Java

C++

Python

Job description

Amazon Science in New York is seeking a senior scientist to design and deploy large-scale optimization and forecasting models that plan inventory and flow across our fulfillment network. You will shape the mathematical architecture of the planning system and push the frontier of solver technology for fast, reliable results.

You will work with cross-functional partners to take ideas from whiteboard to production, owning them end-to-end once live, and contribute to long-term scientific vision in