Data Scientist I, FMA

Description

Every time a customer clicks "Add to Cart" on Amazon, they're trusting us to have already answered a deceptively hard question: out of hundreds of competing offers for the same product, which one is actually the best choice for them right now? Our team owns the algorithm that answers that question — billions of times a day, across every product on Amazon.As a Data Scientist on this team, you'll help make that algorithm smarter. You'll work on the models and signals that rank and surface offers in real time — weighing price, seller performance, fulfillment speed, customer trust signals, and more. The work is technically deep: you're not running one-off analyses, you're building systems that operate at internet scale and directly affect what customers buy and how sellers compete.

You'll run experiments, develop predictive models, and partner with engineers and product managers to turn your findings into features that ship. If you enjoy problems where getting the answer right really matters — for customers, for sellers, and for the business — you'll find a lot to work on here.

Basic Qualifications

- 1+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience- 2+ years of data/research scientist, statistician or quantitative analyst in an internet-based company with complex and big data sources 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)

Preferred Qualifications

- Ph.D. in Science, Technology, Engineering, or Mathematics (STEM)- Knowledge of statistical packages and business intelligence tools such as SPSS, SAS, S-PLUS, or R- Knowledge of machine learning concepts and their application to reasoning and problem-solving- Experience with clustered data processing (e.g., Hadoop, Spark, Map-reduce, and Hive)- Experience working with or evaluating AI systems- Experience applying quantitative analysis to solve business problems and making data-driven business decisions- Experience effectively communicating complex concepts through written and verbal communication