Amazon
Data Scientist , Reactive Transfers
Found: Today
Description
The Supply Chain Optimization Technologies (SCOT) team builds technology to automate and optimize Amazon’s supply chain of physical goods. We seek a Data Scientist with strong analytical and communication skills to join our team. SCOT manages Amazon's inventory under uncertainty of demand, pricing, promotions, supply, vendor lead times, and product life cycle. We optimize complex trade-offs between customer experience, inventory costs, fulfillment costs, fulfillment center capacity, etc. We develop sophisticated algorithms that involve learning from large amounts of data such as prices, promotions, similar products, and other data from our product catalog in order to automatically act on millions of dollars’ worth of inventory weekly and establish plans for tens of thousands of employees.
Basic Qualifications
- 2+ years of data scientist experience- 3+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience- 3+ years of machine learning/statistical modeling data analysis tools and techniques, and parameters that affect their performance experience- 1+ years of guiding and coaching a group of researchers experience- 1+ years of working with or evaluating AI systems experience- 1+ years of creating or contributing to mathematical textbooks, research papers, or educational content experience- Master's degree in Science, Technology, Engineering, or Mathematics (STEM), or experience working in Science, Technology, Engineering, or Mathematics (STEM)- Experience applying theoretical models in an applied environment
Preferred Qualifications
- Ph.D. in Science, Technology, Engineering, or Mathematics (STEM)- Knowledge of machine learning concepts and their application to reasoning and problem-solving- Experience in Python, Perl, or another scripting language- Experience in a ML or data scientist role with a large technology company- Experience in defining and creating benchmarks for assessing GenAI model performance- Experience working on multi-team, cross-disciplinary projects- Experience applying quantitative analysis to solve business problems and making data-driven business decisions- Experience effectively communicating complex concepts through written and verbal communication
