Verified Job
IT / Software / Data Analyst
Senior Applied Scientist, Agentic AI for Data Analytics and Science, Speed Analy
IT / Software / Data Analyst
#652783
Remote / WFH
Job Description
DESCRIPTION
Are you excited by the opportunity to define how Amazon builds and scales intelligent AI systems that influence strategic decisions across a massive transportation network? Do you want to lead the development of agentic AI solutions and mentor the next generation of scientists while shaping how we use generative AI at scale?
Amazon’s North American Transportation Data Science & Analytics team is looking for a Senior Applied Scientist to lead the design and implementation of agentic AI systems that simulate, reason, and deliver insights across Amazon’s dynamic supply chain and delivery operations. You will set scientific direction, define development strategy, and lead by example—building intelligent agents that accelerate our ability to analyze complex data and make customer-centric decisions at scale.
This is a high-impact, highly visible role. You'll collaborate closely with product, engineering, science, and business leaders across planning, forecasting, operations, and last-mile delivery. Delivery speed is one of Amazon’s core customer value propositions and a key differentiator—your work will directly shape how we measure and improve that experience.
Key job responsibilities
Define the AI and agentic development strategy for transportation analytics, including use case prioritization, architecture principles, and integration frameworks
Lead the design and development of autonomous AI agents that deliver insights, simulate system behavior, and support experimentation across analytics workflows
Build systems that allow agents to interact with APIs, knowledge bases, structured and unstructured data sources
Mentor and develop junior scientists and engineers, providing scientific guidance, code reviews, and career development support
Collaborate with Data Scientists, BIEs, and Engineering teams to integrate agentic systems into production workflows and internal tools
Define and own agent evaluation frameworks—measuring business impact, correctness, and efficiency at scale
Drive adoption of shared infrastructure like reusable APIs, prompt libraries, and model registries
Partner with AWS teams and internal technical stakeholders to leverage emerging AI/ML technologies, and serve as an evangelist for scalable, interoperable solutions
Influence cross-org discussions on AI strategy, experimentation tooling, and reusable architecture to support Amazon-wide analytics goals
About the team
We enable data-driven decision-making for Amazon’s North American Transportation network by combining deep analytics, causal modeling, and experimentation. Our team supports business and tech stakeholders across planning, delivery, and customer experience by developing scalable tools, dashboards, and metrics. As we evolve toward agentic and generative AI, we are reimagining how insights are produced—moving from static reports to intelligent, autonomous systems that proactively surface opportunities and drive operational excellence.
BASIC QUALIFICATIONS
3+ years of building machine learning models for business application experience
PhD, or Master's degree and 6+ years of applied research experience
Experience programming in Java, C++, Python or related language
Experience with neural deep learning methods and machine learning
PREFERRED QUALIFICATIONS
Experience with modeling tools such as R, scikit-learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy etc.
Experience with large scale distributed systems such as Hadoop, Spark etc.
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.
Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.
Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $150,400/year in our lowest geographic market up to $260,000/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. For more information, please visit https://www.aboutamazon.com/workplace/employee-benefits. This position will remain posted until filled. Applicants should apply via our internal or external career site.
Are you excited by the opportunity to define how Amazon builds and scales intelligent AI systems that influence strategic decisions across a massive transportation network? Do you want to lead the development of agentic AI solutions and mentor the next generation of scientists while shaping how we use generative AI at scale?
Amazon’s North American Transportation Data Science & Analytics team is looking for a Senior Applied Scientist to lead the design and implementation of agentic AI systems that simulate, reason, and deliver insights across Amazon’s dynamic supply chain and delivery operations. You will set scientific direction, define development strategy, and lead by example—building intelligent agents that accelerate our ability to analyze complex data and make customer-centric decisions at scale.
This is a high-impact, highly visible role. You'll collaborate closely with product, engineering, science, and business leaders across planning, forecasting, operations, and last-mile delivery. Delivery speed is one of Amazon’s core customer value propositions and a key differentiator—your work will directly shape how we measure and improve that experience.
Key job responsibilities
Define the AI and agentic development strategy for transportation analytics, including use case prioritization, architecture principles, and integration frameworks
Lead the design and development of autonomous AI agents that deliver insights, simulate system behavior, and support experimentation across analytics workflows
Build systems that allow agents to interact with APIs, knowledge bases, structured and unstructured data sources
Mentor and develop junior scientists and engineers, providing scientific guidance, code reviews, and career development support
Collaborate with Data Scientists, BIEs, and Engineering teams to integrate agentic systems into production workflows and internal tools
Define and own agent evaluation frameworks—measuring business impact, correctness, and efficiency at scale
Drive adoption of shared infrastructure like reusable APIs, prompt libraries, and model registries
Partner with AWS teams and internal technical stakeholders to leverage emerging AI/ML technologies, and serve as an evangelist for scalable, interoperable solutions
Influence cross-org discussions on AI strategy, experimentation tooling, and reusable architecture to support Amazon-wide analytics goals
About the team
We enable data-driven decision-making for Amazon’s North American Transportation network by combining deep analytics, causal modeling, and experimentation. Our team supports business and tech stakeholders across planning, delivery, and customer experience by developing scalable tools, dashboards, and metrics. As we evolve toward agentic and generative AI, we are reimagining how insights are produced—moving from static reports to intelligent, autonomous systems that proactively surface opportunities and drive operational excellence.
BASIC QUALIFICATIONS
3+ years of building machine learning models for business application experience
PhD, or Master's degree and 6+ years of applied research experience
Experience programming in Java, C++, Python or related language
Experience with neural deep learning methods and machine learning
PREFERRED QUALIFICATIONS
Experience with modeling tools such as R, scikit-learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy etc.
Experience with large scale distributed systems such as Hadoop, Spark etc.
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.
Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.
Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $150,400/year in our lowest geographic market up to $260,000/year in our highest geographic market. Pay is based on a number of factors including market location and may vary depending on job-related knowledge, skills, and experience. Amazon is a total compensation company. Dependent on the position offered, equity, sign-on payments, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits. For more information, please visit https://www.aboutamazon.com/workplace/employee-benefits. This position will remain posted until filled. Applicants should apply via our internal or external career site.
