Principal Applied Scientist, Supply Chain Efficiency

2 weeks ago


Bellevue, Washington, United States Amazon Full time

Overview:
Have you ever considered how Amazon accurately forecasts delivery times and ensures that orders arrive as promised? Are you driven by the desire to enhance operational efficiency while minimizing environmental impact? If the prospect of influencing Amazon's global logistics network excites you, we would like to connect with you.

About the Role:
The Fulfillment Planning & Execution (FPX) Science team within Amazon's Supply Chain Optimization Technologies (SCOT) is on the lookout for a Senior Applied Scientist with a strong background in Machine Learning and a history of delivering scalable solutions to complex business challenges.

This team is dedicated to addressing some of the most intricate mathematical problems in transportation planning and execution, aiming to elevate Amazon's operational effectiveness on a global scale. We are responsible for the planning and execution of Amazon's worldwide fulfillment centers and transportation systems.

Key Responsibilities:
As a Senior Applied Scientist in the FPX Science team, you will:

  • Develop and implement innovative ML models to tackle intricate business challenges.
  • Research and integrate cutting-edge ML techniques from both academic and industry sources.
  • Focus on enhancing the customer delivery experience.
  • Utilize analytical methods to create scalable solutions for business issues.
  • Collaborate closely with software engineering teams to deploy models and algorithms at scale.
  • Provide technical leadership and mentorship to fellow scientists.
  • Establish efficient, automated processes for large-scale data analysis, model development, validation, and implementation.

A Day in the Life:
This position offers a unique opportunity to delve into Amazon's logistics network, encompassing Fulfillment Centers, Air Stations, Sort Centers, and Delivery Stations. You will engage with various internal stakeholders to comprehend their business needs and challenges, facilitating the development of effective solutions.

Our leadership values this initiative, providing ample opportunities to present your ideas for evaluation and alignment. We seek individuals who are eager to lead projects that require innovative thinking and advanced technical problem-solving skills to create production-ready machine learning solutions.

About the Team:
The FPX Science team comprises a diverse group of scientists with expertise in Machine Learning and Operations Research, collaborating closely on projects. We directly support essential functional areas across Fulfillment Optimization and address the research needs of product and engineering teams.

Our mission is to tackle some of the most mathematically challenging issues in facility and transportation planning, enhancing Amazon's operational efficiency at an unparalleled scale. We strive to apply hybrid techniques in Operations Research and Machine Learning to address significant technical challenges.

Qualifications:
To be successful in this role, candidates should possess:

  • A PhD in a quantitative field such as econometrics, statistics, industrial engineering, or operations research.
  • 5+ years of experience in building machine learning models for business applications.
  • Proficiency in programming languages such as Java, C++, or Python.
  • Experience with modeling tools like R, scikit-learn, Spark MLLib, TensorFlow, and others.
  • Strong problem-solving skills and the ability to communicate effectively with both technical and non-technical stakeholders.

Amazon is committed to fostering a diverse and inclusive workplace. We are an equal opportunity employer and do not discriminate based on race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status.



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