Overview In this role you will develop and deploy optimization- and ML-driven solutions to optimize Amazon's outbound transportation planning and execution. You will translate business needs into mathematical models and scalable production systems, working with cross-functional partners to drive impact. You will lead and mentor scientists, establish automated data analyses and model validation processes, and push state-of-the-art methods in a high-scale environment. Join a team tackling complex supply chain planning to improve global fulfilment efficiency and customer delivery experience.
Compensation / Benefits- health insurance (medical, dental, vision)
- 401(k) matching
- paid time off
- parital leave options
- RSUs
- sign-on payments
Responsibilities- Design, development and evaluation of innovative mathematical models for solving complex business problems
- Research and apply the latest optimization techniques and best practices from academia and industry
- Focus on improving the customer delivery experience and scalable solutions for business problems
- Use analytical techniques to create scalable, production-ready solutions
- Collaborate with software engineering teams to implement models in production systems at large scale
- Technically lead and mentor other scientists in the team
- Establish automated, scalable processes for data analyses, model development, validation and deployment
Key requirements- 5+ years of applied research experience
- Experience programming in Java, C++, Python or related language
- 5+ years of industry or academic research experience
- Ph.D. in the specified fields
- 5+ years of mathematics optimization experience (linear and nonlinear)
- Experience hiring and developing junior members
- Knowledge of problem solving, algorithm design and complexity analysis
- collaborative problem solving
- leadership and mentorship
- strong communication and stakeholder engagement
- Mathematical optimization (linear and nonlinear)
- Machine learning and statistical modeling
- Graph models
