Research Scientist II - ML & Optimization for Supply Chains

Amazon Science; New York (NY); On-site; USD 158,000 - 213,000; Full time

Job summary

Amazon Science in New York seeks a Research Scientist II to develop scalable machine learning systems and optimization models for supply chain and logistics. You will implement models in Python, C++, or Java, write data-gathering scripts, and simulate operations to inform decisions.

The role requires strong background in operations research and programming, with experience solving optimization problems and delivering production-ready prototypes.

Qualifications

• Master's degree or foreign equivalent in OR/CS/Engineering/Math with 1 year related experience, or Bachelor's with 5 years equivalent experience and 1 year in related roles.
• Proficiency in Java, C++, C#, C, or Python for programming and optimization.
• Experience formulating and solving discrete and continuous optimization problems.

Responsibilities

• Develop scalable machine learning systems and optimization models to improve operations.
• Build mathematical models for supply chain, transport, and logistics systems.
• Write ad-hoc scripts and queries to gather data for analysis and modeling.
• Create simulations to support operational decision-making and test methodologies.
• Integrate prototypes into production systems using standard software tools.

Skills

Java

C++

C#

C

Python

Optimization

Operations Research

Education

Master's degree in Operations Research / Computer Science / Engineering / Mathematics

Bachelor's degree + 5 years progressive experience

Tools

SQL

Job description

Amazon Science in New York seeks a Research Scientist II to develop scalable machine learning systems and optimization models for supply chain and logistics. You will implement models in Python, C++, or Java, write data-gathering scripts, and simulate operations to inform decisions.

The role requires strong background in operations research and programming, with experience solving optimization problems and delivering production-ready prototypes.