Amazon Last Mile builds global solutions that enable Amazon to attract an elastic supply of drivers, companies, and assets needed to deliver Amazon's and other shippers' volumes at the lowest cost and with the best customer delivery experience. Last Mile Science team owns the core decision models in the space of jurisdiction planning, delivery channel and modes network design, capacity planning for on the road and at delivery stations, routing inputs estimation and optimization. We also own scalable solutions to reduce risks, improve safety, enhance personalized experiences of our delivery associates and partners. Our research has direct impact on customer experience, driver and station associate experience, Delivery Service Partner (DSP)’s success and the sustainable growth of Amazon.

We are looking for a passionate individual with strong machine learning and analytical skills to join its Last Mile Science team in the endeavor of designing and improving the most complex planning of delivery network in the world. As a Senior Applied Scientist, you will work with software engineers, product managers, and business teams to understand the business problems and requirements, distill that understanding to crisply define the problem, and design and develop innovative solutions to address them. Our team is highly cross-functional and employs a wide array of scientific tools and techniques to solve key challenges, including supervised and unsupervised machine learning, non-convex optimization, causal inference, natural language processing, linear programming, reinforcement learning, and other forecast algorithms.


Key job responsibilities
Key job responsibilities
* Drive end-to-end Machine Learning projects that have a high degree of ambiguity, scale and complexity.
* Build Machine Learning models, perform proof-of-concept, experiment, optimize, and deploy your models into production; work closely with software engineers to assist in productionizing your ML models.
* Run A/B experiments, gather data, and perform statistical analysis.
* Measure and estimate risks, constructively critique peer research, and align research focuses with the Amazon's strategic needs.
* Research new and innovative machine learning approaches. Help coach/mentor junior scientists in the team.
* Willingness to publish research at internal and external top scientific venues. Write and pursue IP submissions.