Data Scientist, Amazon

• The ideal candidate has strong fundamentals in forecasting and applied ML, experience with Python and SQL, comfort working with large-scale retail datasets, and the ability to communicate findings clearly to non-technical partners
• 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)

Desirable

• This role is on the Core Tech Private Brands Analytics (PBA) team, a cross-functional team (software engineering, data science, data engineering, business intelligence) that owns Amazon Private Brands (APBs) central data infrastructure and builds platforms and models that help improve business performance
• In this job you will build and improve forecasting and planning models across APB, partnering with business, science, and tech stakeholders
• Day-to-day work includes end-to-end pipeline development (feature engineering through training and deployment) on SageMaker, S3, and Datanet, replacing manual spreadsheet-driven processes with reproducible code-driven pipelines and dashboards, evaluating model accuracy across business segments, and contributing to APB's science standards alongside a senior scientist assessing the org's AI framework and experimentation rigor