Data Scientist, NA Operations
Amazon (AI roles) · Bellevue, Washington, USA
No salary listed. Estimated from 366 salary-disclosed Research roles on this board: $224K–$330K (interquartile range; estimate, not the employer's figure).
Apply at Amazon (AI roles)Find your warm intro on LinkedInAbout the role
Within Amazon's North American Operations, we are tackling mission-critical problems to optimize network operations. We build complex causal, forecasting, and optimization models to better understand, predict, and govern processes across hundreds of warehouses. We are seeking a Data Scientist to drive the development of these models, deeply integrate with business stakeholders, and leverage generative AI to more intelligently build for our customers.
Key job responsibilities
- Interfacing with stakeholders to understand business problems and translating these into high and low-level design documents.
- Building machine learning, optimization, and causal inference models that target business-specific challenges.
- Sourcing, cleaning, and analyzing large and complex data sets associated with warehouse operations to provide business-critical insights at scale.
- Leveraging AI-based solutions to drive development and provide nuanced insights into model outcomes.
A day in the life
You will be a single-threaded owner of projects within Amazon Operations, owning project scoping, stakeholder engagement, data enablement, and model development. Your work will be directly consumed by partner teams throughout Operations and Finance, and hence a strong sense of ownership is required to educate both technical and non-technical stakeholders on developed science solutions.
About the team
Our team is comprised of Data Scientists, Applied Scientists, and Economists, and are trusted to make data-driven solutions that power operations decision making. We strive to build consensus on divisive topics through clear presentation of problem statements paired with deep analyses that gain visibility throughout all levels of the organization from operators to executives. - 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
- Master's degree in Science, Technology, Engineering, or Mathematics (STEM), or experience working in Science, Technology, Engineering, or Mathematics (STEM)
Key job responsibilities
- Interfacing with stakeholders to understand business problems and translating these into high and low-level design documents.
- Building machine learning, optimization, and causal inference models that target business-specific challenges.
- Sourcing, cleaning, and analyzing large and complex data sets associated with warehouse operations to provide business-critical insights at scale.
- Leveraging AI-based solutions to drive development and provide nuanced insights into model outcomes.
A day in the life
You will be a single-threaded owner of projects within Amazon Operations, owning project scoping, stakeholder engagement, data enablement, and model development. Your work will be directly consumed by partner teams throughout Operations and Finance, and hence a strong sense of ownership is required to educate both technical and non-technical stakeholders on developed science solutions.
About the team
Our team is comprised of Data Scientists, Applied Scientists, and Economists, and are trusted to make data-driven solutions that power operations decision making. We strive to build consensus on divisive topics through clear presentation of problem statements paired with deep analyses that gain visibility throughout all levels of the organization from operators to executives. - 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
- Master's degree in Science, Technology, Engineering, or Mathematics (STEM), or experience working in Science, Technology, Engineering, or Mathematics (STEM)
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