Join an elite analytics tiger team within Amazon's External Fulfillment (EF) organization as a Data Scientist, where you'll partner with Senior Business Intelligence Engineers and fellow Data Scientists to tackle some of the most complex and ambiguous challenges facing Amazon's supply chain. As part of this high-impact team, you'll apply sophisticated statistical methods and machine learning approaches to decode previously unsolved operational puzzles. This role combines advanced quantitative expertise with innovative problem-solving to transform undefined challenges into structured, data-driven solutions.
Working closely with your BIE counterparts, who will build robust data infrastructure to support your models, you'll develop sophisticated analytical solutions that drive multi-million dollar decisions across our fulfillment network. You'll have the freedom to explore advanced statistical and machine learning techniques while having direct visibility and impact on Amazon's most strategic supply chain initiatives.
Key job responsibilities
- Design and implement sophisticated statistical and machine learning models to solve complex supply chain problems
- Partner with BIEs to define data requirements and ensure optimal data architecture for model development
- Apply a range of data science methodologies to conduct analysis for cases where solution approaches are unclear
- Develop and validate hypotheses through rigorous statistical testing and experimentation
- Create scalable algorithms that can be deployed across our fulfillment network
- Build predictive models to optimize operational decision-making
- Communicate complex analytical findings to technical and non-technical stakeholders
- Collaborate in data discovery initiatives to uncover new business opportunities
- Contribute to the team's scientific strategy and methodological approaches
A day in the life
Your morning might begin collaborating with your BIE partner to define data requirements for a new network optimization model. You'll then develop and test statistical approaches for identifying operational inefficiencies, working closely with business stakeholders to validate your findings. By afternoon, you could be prototyping machine learning models for demand forecasting, followed by presenting your methodology and results to leadership. You'll end your day brainstorming with your tiger team on novel approaches to solving complex supply chain challenges.
About the team
The EF Data Team is a critical, multifaceted group that provides end-to-end data support, analytics, and innovative data-driven solutions across EF's five key business verticals: Operations, Business Growth, Business Optimization, Operational Excellence, and Product Development. Structured with Business Intelligence Engineers (BIEs) focused on advanced analytics and pipeline development, Business Analysts (BAs) dedicated to building domain-specific tools and reporting, and data scientists building predictive models, the team takes a thoughtful, collaborative approach to their work. They foster a culture that values learning, candor, and positive encouragement, ensuring clear communication and a shared understanding of problem statements, success metrics, and expected deliverables. Committed to maintaining a high bar of excellence, the team devotes the necessary time and resources to produce reliable, scalable data solutions that can be leveraged across the growing EF organization. They prioritize work that drives to the root causes of high-impact business challenges, streamlining data access, developing self-service analytics tools, and continuously expanding their analytical capabilities to better serve their stakeholders.
