Amazon's External Fulfillment (EF) organization is looking to solve complex and ambiguous challenges facing Amazon's supply chain by applying sophisticated statistical methods and machine learning approaches.
Requirements
- 5+ years of data querying languages (e.g. SQL), scripting languages (e.g. Python) or statistical/mathematical software (e.g. R, SAS, Matlab, etc.) experience
- 4+ years of data scientist experience
- Experience with statistical models e.g. multinomial logistic regression
- 2+ years of data visualization using AWS QuickSight, Tableau, R Shiny, etc. experience
- Experience managing data pipelines
- Experience as a leader and mentor on a data science team
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
Other
- Collaborate in data discovery initiatives to uncover new business opportunities
- Contribute to the team's scientific strategy and methodological approaches
- Communicate complex analytical findings to technical and non-technical stakeholders
- 4+ years of data scientist experience
- Ability to work in a team environment
