Principal Research Scientist, Fulfillment Planning and Execution Science

4 weeks ago

Bellevue, United States Amazon.com Services LLC Full time
Amazon Fulfillment Planning & Execution (FPX) Science team within Supply Chain Optimization Technologies (SCOT) Fulfilment Optimization group is seeking a Principal Research Scientist with expertise in Machine Learning and a proven record of solving business problems through scalable ML solutions. Network Planning and Fulfillment Execution tackles some of the most mathematically complex challenges in facility and transportation planning to improve Amazon's operational efficiency worldwide. We own Amazon’s global fulfillment center and transportation topology planning and execution. The team also owns the short-term network planning that determines the optimal flow of customer orders through Amazon fulfillment network. This includes developing sophisticated math models and controllers that assign orders to fulfillment centers to be picked and packed and then planning the optimal ship method in terms of cost, speed and carbon impact to deliver to the customer. These plans drive downstream decisions that are in the billions of dollars. The systems we build are entirely in-house, and are on the cutting edge of both academic and applied research in large scale supply chain planning, optimization, machine learning and statistics. These systems operate at various scales, from real-time decision system that completes thousands of transactions per seconds, to large scale distributed system that optimize Amazon’s fulfillment network. As Amazon continues to build and expand the first party delivery network, this role will be critical to realize this vision. Your tech solution will have large impacts to the physical supply chain of Amazon, and play a key role in improving Amazon consumer business’s long-term profitability. If you are interested in diving into a multi-discipline, high impact space this is the team for you.

Key job responsibilities
As a Principal Research Scientist within FPX Science team, you will propose and deploy solutions that will likely draw from a range of scientific areas such as supervised, semi-supervised and unsupervised learning, reinforcement learning, advanced statistical modeling, and graph models. You will have an opportunity to be on the forefront of supply chain thought leadership by working on some of the most difficult problems in the industry, with some of the best product managers, research scientists, statisticians, and software engineers to integrate scientific work into production systems. You will partner with the senior tech leaders in the organization to define the long-term vision of our Network Planning and Fulfillment Execution systems. You will play a key role in developing long term strategic solutions that have business impact beyond the scope of the organization. You will bring deep technical expertise in the area of Machine Learning, and will play an integral part in building Amazon's Fulfillment Optimization systems. Other responsibilities include:
•Research and develop machine learning models to solve diverse business problems faced within Network Planning and Fulfillment Execution team.
•Drive and execute machine learning projects/products end-to-end: from ideation, analysis, prototyping, development, metrics, and monitoring.
•Review and audit modeling processes and results for other scientists, both junior and senior.
•Advocate the right ML solutions to business stakeholders, engineering teams, as well as executive level decision makers
•You will ensure senior leaders in the organization are up to speed on important trends, tools and technologies and how they will be used to impact the business.

A day in the life
In this role, you will be a technical leader in machine learning with significant scope, impact, and high visibility. Your solutions will impact business segments worth many-billions-of-dollars and geographies spanning multiple countries and markets. As a Principal Research Scientist on the team, you will be involved in every aspect of the process - from ideation, business analysis and scientific research, through to development and deployment of advanced models - giving you a real sense of ownership. From day one, you will be working with bar raising scientists, engineers, and designers. You are expected to make decisions about technology, models and methodology choices. You will also collaborate with the broader science community in Amazon to broaden the horizon of your work and mentor engineers and other scientists. We are seeking someone who wants to lead projects that require innovative thinking and deep technical problem-solving skills to create production-ready machine learning solutions. A successful candidate is able to quickly approach large ambiguous problems, turn high-level business requirements into mathematical models, identify the right solution approach, and contribute to the software development for production systems. Successful candidates must thrive in fast-paced environments, which encourage collaborative and creative problem solving, be able to measure and estimate risks, constructively critique peer research, and align research focuses with the Amazon's strategic needs. We look for individuals who know how to deliver results and show a desire to develop themselves, their colleagues, and their career.

About the team
FPX Science team contains a group of scientists with different technical backgrounds including Machine Learning and Operations Research, who will collaborate closely with you on your projects. Our team directly supports multiple functional areas across Fulfillment Optimization and the research needs of the corresponding product and engineering teams. We tackle some of the most mathematically complex challenges in facility and transportation planning to improve Amazon's operational efficiency worldwide and at a scale that is unique to Amazon. We often seek the opportunity of applying hybrid techniques in the space of Operations Research and Machine Learning to tackle some of our biggest technical challenges. We disambiguate complex supply chain problems and create ML and optimization solutions to solve those problems at scale.

We are open to hiring candidates to work out of one of the following locations:

Bellevue, WA, USA

BASIC QUALIFICATIONS

- 10+ years of tech industry or equivalent experience
- PhD in a quantitative discipline such as statistics, mathematics, economics, computer science, or any related quantitative field
- Experience working effectively with science, data processing, and software engineering teams

PREFERRED QUALIFICATIONS

- Experience implementing models and tools through the use of high-level modeling languages (AMPL, Mosel, R, Matlab, Julia)

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