Applied Scientist, NA Operations
Amazon (AI roles) · Bellevue, Washington, USA
No salary listed. Estimated from 386 salary-disclosed Research roles on this board: $223K–$326K (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 that center on improving employee safety and productivity. We build complex causal, forecasting, and optimization models to understand, predict, and optimize our network operations. We are seeking an Applied Scientist to drive the operational excellence of these models, deeply integrate across Amazon systems, and leverage generative AI to more intelligently build for our customers.
Check out the hiring managers LinkedIN article - https://www.linkedin.com/pulse/from-nuclear-power-network-intelligence-david-plews-brittany-sdkbe/
Key job responsibilities
- Interfacing with stakeholders to understand business problems and translating these into high and low-level design documents.
- Architecting, building, and deploying production-grade models to cloud-native environments, incorporating CI/CD best practices.
- Designing AI systems to provide model explainability, as well as automate customer workflows.
- Developing evaluation frameworks for models that identify quality regressions before customers do.
A day in the life
You will be a single-threaded owner of projects within Amazon Operations, owning project scoping, stakeholder engagement, data enablement, model development, and production launches. 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. - Currently has, or is in the process of obtaining, a Master's degree or above in computer science, machine learning, engineering, or related fields
- Experience programming in Java, C++, Python or related language
- Experience with SQL and an RDBMS (e.g., Oracle) or Data Warehouse
- Experience in building machine learning models for business application
Check out the hiring managers LinkedIN article - https://www.linkedin.com/pulse/from-nuclear-power-network-intelligence-david-plews-brittany-sdkbe/
Key job responsibilities
- Interfacing with stakeholders to understand business problems and translating these into high and low-level design documents.
- Architecting, building, and deploying production-grade models to cloud-native environments, incorporating CI/CD best practices.
- Designing AI systems to provide model explainability, as well as automate customer workflows.
- Developing evaluation frameworks for models that identify quality regressions before customers do.
A day in the life
You will be a single-threaded owner of projects within Amazon Operations, owning project scoping, stakeholder engagement, data enablement, model development, and production launches. 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. - Currently has, or is in the process of obtaining, a Master's degree or above in computer science, machine learning, engineering, or related fields
- Experience programming in Java, C++, Python or related language
- Experience with SQL and an RDBMS (e.g., Oracle) or Data Warehouse
- Experience in building machine learning models for business application
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