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Data Scientist II, Amazon Fulfillment Technology (AFT) Science

Amazon

Data Scientist II, Amazon Fulfillment Technology (AFT) Science

full-timePosted: Aug 17, 2026Updated: Aug 27, 2026Bellevue, Washington, United States

Job Description

The Amazon Fulfillment Technologies (AFT) Science team is looking for an exceptional Data Scientist, with strong analytical skills and understanding of optimization, to partner with scientists, engineers, product managers, and operations leaders, and develop data-driven solutions for one of the most complex systems in the world: Amazon’s Fulfillment Network. At AFT Science, we design, build and deploy optimization, simulation, and machine learning solutions to power the production systems running at world wide Amazon Fulfillment Centers. We solve a wide range of problems that are encountered in the network, including labor planning and staffing, demand prioritization, stow guidance, pick scheduling, and flow process optimization. We are tasked to develop innovative, scalable, and reliable science-driven solutions that are beyond the published state of art in order to run frequently (ranging from every few minutes to every few hours per use case) and continuously in our large scale network. Key job responsibilities Key job responsibilities As an Data Scientist, you will work with other scientists, software engineers, product managers, and operations leaders to develop scientific solutions and analytics using a variety of tools and observe direct impact to process efficiency and associate experience in the fulfillment network. Key responsibilities include: - Design and conduct rigorous experimental design for production pilots to evaluate the impact of the solution and improve model performance - Lead the end-to-end lifecycle of forecasting models, from research and experimentation through production launch including defining success metrics, obtaining stakeholder sign-off, and managing rollout - Develop and deploy production grade ML and statistical models using Python, Scala, SQL, and related tools - Perform large-scale exploratory data analysis to uncover patterns, identify opportunities, and inform model development - Translate complex science findings into clear insights and recommendations for technical and non-technical stakeholders at all levels - Contribute to Amazon's scientific community and the broader research field through collaboration and presentation in top-tier venues About the team Amazon Fulfillment Technology (AFT) designs, develops and operates the end-to-end fulfillment technology solutions for all Amazon Fulfillment Centers (FC). We harmonize the physical and virtual world so Amazon customers can get what they want, when they want it. The AFT Science team has expertise in operations research, optimization, statistics, simulation, and machine learning. We also have domain expertise in the operational processes within the FCs and their defects. We prioritize advancements that support AFT tech teams and focus areas rather than specific fields of research or individual business partners. We influence each stage of innovation from inception to deployment which includes both developing novel solutions or improving existing approaches. Resulting production systems rely on a diverse set of technologies, our teams therefore invest in multiple specialties as the needs of each focus area evolves.

Locations

  • Bellevue, Washington, United States

Salary

136,000 - 184,000 USD / yearly

Skills Required

  • forecastingintermediate
  • Pythonintermediate

Required Qualifications

  • Bachelor's degree or above in a quantitative field, or Master's degree (degree in above in a quantitative field)
  • 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 (experience, 3 years)
  • 3+ years of machine learning/statistical modeling data analysis tools and techniques, and parameters that affect their performance experience (experience, 3 years)
  • Experience processing, filtering, and presenting large quantities (hundreds of millions/billions of rows) of data (experience)
  • Experience with forecasting and statistical analysis (experience)

Preferred Qualifications

  • Experience in Python, Perl, or another scripting language (experience)
  • 2+ years of ML or optimization and algorithms implementation experience (experience, 2 years)
  • Experience effectively communicating complex concepts through written and verbal communication (experience)
  • Ability to write and maintain production level code is a plus (experience)
  • Ability to maintain end to end data pipelines and metrics at scale (experience)
  • Experience working on multi-team, cross-disciplinary projects (experience)

Responsibilities

  • Design and conduct rigorous experimental design for production pilots to evaluate the impact of the solution and improve model performance
  • Lead the end-to-end lifecycle of forecasting models, from research and experimentation through production launch including defining success metrics, obtaining stakeholder sign-off, and managing rollout
  • Develop and deploy production grade ML and statistical models using Python, Scala, SQL, and related tools
  • Perform large-scale exploratory data analysis to uncover patterns, identify opportunities, and inform model development
  • Translate complex science findings into clear insights and recommendations for technical and non-technical stakeholders at all levels
  • Contribute to Amazon's scientific community and the broader research field through collaboration and presentation in top-tier venues

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