Have you ever ordered a product on Amazon and when that box with the smile arrived you wondered how it got to you so fast? Have you wondered where it came from and how much it cost Amazon to deliver it to you? Have you also wondered what are different ways that the transportation assets can be used to delight the customer even more.
If so, the Amazon transportation Services, Product and Science is for you. We manage the delivery of tens of millions of products every week to Amazon’s customers, achieving on-time delivery in a cost-effective manner through optimizing the network flow, producing accurate forecasting using advanced algorithms. In addition, the team is exploring GenAI/LLM to build the next-generation agent framework to answer "why" in business review and metrics deep-dives.
We are looking for an enthusiastic, customer obsessed, Applied Scientist with strong scientific thinking, good software and statistics experience, skills to help manage projects and operations, improve metrics, and develop scalable processes and tools.
Ideal candidates will be:
- A high potential, strategic and analytic graduate with a PhD in (Operations Research, Statistics, Engineering, and Supply Chain) ready for challenging opportunities in the core of our world class operations space;
- Experience with integer programming, network design, graph modeling, Deep Learning and AI/LLM experience;
- Experience programming in Python, Javascript, C++, or related language.
Key job responsibilities
We are looking for a talented Applied Scientist to address business challenges in the operations world. The key responsibilities and modeling themes are:
- Enable optimization use cases, and improve existing methodologies for better customer experiences using state-of-the-art techniques in ML/DL;
- Work on the forecasting model architecture design, implementation, and delivery of analytical and modeling solutions to support network-level planning;
- Take a lead on new initiatives in AI development with LLM agent framework, and promote efficiency for the org from high-level business summary to metric deep-dive.
