Data Scientist, Amazon Fresh Grocery

Cupertino, California, USA

Full Time Senior-level / Expert USD 68K - 135K * logo

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Job summary
Amazon Fresh Grocery (AFG) is searching for an inventive and deeply curious Data Scientist to join our Retail Science team. Your objective is to explore complex Grocery data, build models, and develop research that dramatically increase the speed and quality of decision-making and automate actions that surprise and delight customers. You will have the opportunity to develop best-in-class business acumen across Retail, Operations, and Supply Chain covering topics such as Pricing, Selection, Vendor Negotiations, Instock Management, Merchandising, Promotions, Store Design & Development, Scaling, Hubs & Distribution, and more.

A successful candidate has a diverse analytical background, a deep curiosity for what drives business planning and execution, and an inventive spirit to create new things. They will be well-versed in modern tools and frameworks for data science and engineering and have proven experience in statistical applications.

Key job responsibilities
  • Build and improve upon data and algorithmic models to make predictions and estimate causal relationships that drive business decisions and automate actions
  • Design and execute experiments to test business hypotheses
  • Write white papers to describe scientific approaches for modeling business problems and making recommendations that influence technical and non-technical audiences and that support funding for large-scale R&D initiatives
  • Build relationships with fellow scientists, engineers, and business teams to collaborate cross-functionally and cross-organizationally on critical research programs

Basic Qualifications

  • Master’s degree in a quantitative field (Computer Science, Mathematics, Machine Learning, AI, Statistics, Operations Research, or equivalent) or equivalent experience as a Data Scientist
  • 2+ years of professional experience extracting/transforming/processing data and implementing statistical methods using scripting and/or programming languages (e.g., SQL, Python, R, Matlab, STATA)
  • Proven experience building data and/or algorithmic models to make predictions and/or estimate causal relationships, particularly in a business context
  • Proven experience in experiment design and execution for hypothesis testing
  • Strong verbal and written communication skills to communicate scientific concepts and applications to technical and non-technical audiences

Preferred Qualifications

  • PhD in quantitative field (Computer Science, Mathematics, Machine Learning, AI, Statistics, Operations Research, or equivalent)
  • Strong background in causal inference and/or time series forecasting applications
  • Experience with data visualization software such as Tableau, Amazon Quicksight
  • Experience with AWS technologies (SageMaker, Redshift, RDS, S3, EMR, etc.) and Hadoop ecosystems (Spark, MapReduce, YARN, Hive, etc.)
  • Experience working in supply chain, retail, and/or consumables industry

Amazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status. For individuals with disabilities who would like to request an accommodation, please visit
* Salary range is an estimate based on our salary survey at
Job region: North America
Job country: United States
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