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DESCRIPTION

Amazon's Supply Chain Optimization Technologies (SCOT) group is at the forefront of applying machine learning to transformative real-world problems. We are seeking a talented Applied Scientist to join the Selection team. The Selection team makes assortment decisions across both WW limited shelf program formats (such as speed programs offering 4 hour deliver in US) and retail offerings to balance profitability and customer experience.

As an Applied Scientist in SCOT, you will be working alongside thought science and engineering leaders, contributing to academic research and complex, real-world applications. Your work will directly influence Amazon's assortment decisions, shaping decisions that affect billions of dollars worth of inventory and a wide array of product lines. You are an analytical problem solver who enjoys diving into data from various businesses, is excited about investigations and algorithms, can multi-task, and can credibly interface between scientists, engineers and business stakeholders. Your expertise in synthesizing and communicating insights and recommendations to audiences of varying levels of technical sophistication will enable you to answer specific business questions and innovate for the future.

Key job responsibilities
· Analysis of large amounts of data from different parts of the supply chain and their associated business functions
· Improving upon existing machine learning methodologies by developing new data sources, developing and testing model enhancements, running computational experiments, and fine-tuning model parameters for new models
· Formalizing assumptions about how models are expected to behave, creating definitions of outliers, developing methods to systematically identify these outliers, and explaining why they are reasonable or identifying fixes for them
· Communicating verbally and in writing to business customers with various levels of technical knowledge, educating them about our research, as well as sharing insights and recommendations
· Utilizing code (Python, R, Scala, etc.) for analyzing data and building statistical and machine learning models and algorithms

Key job responsibilities
You will be an end-to-end owner for the projects you support. Responsibilities include:
- Understanding business requirements and existing challenges and map them to the right scientific solution;
- Designing effective, scalable, and achievable solutions to key business problems;
- Developing the right set of metrics to evaluate efficacy of your models and solutions;
- Prototyping and analyzing new models and business logic;
- Productionizing your scientific solutions, including writing production-quality critical path code;
- Communicating, both written and verbally, with both technical and business audiences throughout each project;
- Publishing findings in internal and/or external conferences and interfacing with the scientific community;
- Mentoring and developing the scientist community across the organization