Applied Scientist, SCOT Customer Instock Value
Applied Scientist, SCOT Customer Instock Value
Posted on :
25-05-2025
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1 Vacancy
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Job Description
Are you passionate about applying causal inference and machine learning techniques to revolutionize how Amazon makes inventory decisions Do you want to be part of a team thats reinventing how we measure the long-term impact of product availability on customer behavior throughout their entire shopping journey
The Consumer Instock Value (CIV) team within Amazons Supply Chain Optimization Technology (SCOT) Group develops and manages systems that estimate the long-term impact of inventory availability and delivery speed changes at the product level. Our estimates are crucial inputs for multiple production systems across Amazons supply chain planning helping teams make critical decisions about inventory management selection and placement.
We are seeking applied scientists to help shape our next-generation vision of modernizing how we estimate the impact of inventory decisions through innovative applications of machine learning and causal inference. We aim to create more accurate scalable and robust solutions that can adapt to Amazons evolving customer shopping patterns and business needs.
Key responsibilities include:
- Developing innovative approaches that combine state-of-the-art AI/ML with causal inference to estimate individual treatment effects
- Creating sophisticated frameworks that capture customer journey interactions and cross-product patterns using sequential data
- Designing and implementing validation approaches using experiments quasi-experimental methods and simulations
- Building scalable architectures capable of processing multiple customer interaction data streams
- Collaborating with other scientists and technical teams to implement production systems that can process complex customer journey data
- Leading research initiatives to resolve scientific ambiguities in applying ML methods to causal inference problems
- Presenting findings to stakeholders and contributing to Amazons research paradigms
The ideal candidate will have:
- Deep expertise in causal inference and machine learning
- Experience with large-scale data processing and modeling
- Strong research background in econometrics or related fields
- Ability to bridge theoretical foundations with practical implementations
- Excellence in communicating complex technical concepts to diverse audiences
Your work will directly impact critical business decisions across Amazons retail business helping optimize the balance between inventory costs and customer experience while contributing to scientific developments in the intersection of machine learning and causal inference.
- 2 years of building models for business application experience
- PhD or Masters degree and 2 years of CS CE ML or related field experience
- Experience programming in Java C Python or related language
- Experience in any of the following areas: algorithms and data structures parsing numerical optimization data mining parallel and distributed computing high-performance computing
- Experience using Unix/Linux
- Experience in professional software development
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 for more information. If the country/region youre applying in isnt 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 $136000/year in our lowest geographic market up to $223400/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 This position will remain posted until filled. Applicants should apply via our internal or external career site.
The Consumer Instock Value (CIV) team within Amazons Supply Chain Optimization Technology (SCOT) Group develops and manages systems that estimate the long-term impact of inventory availability and delivery speed changes at the product level. Our estimates are crucial inputs for multiple production systems across Amazons supply chain planning helping teams make critical decisions about inventory management selection and placement.
We are seeking applied scientists to help shape our next-generation vision of modernizing how we estimate the impact of inventory decisions through innovative applications of machine learning and causal inference. We aim to create more accurate scalable and robust solutions that can adapt to Amazons evolving customer shopping patterns and business needs.
Key responsibilities include:
- Developing innovative approaches that combine state-of-the-art AI/ML with causal inference to estimate individual treatment effects
- Creating sophisticated frameworks that capture customer journey interactions and cross-product patterns using sequential data
- Designing and implementing validation approaches using experiments quasi-experimental methods and simulations
- Building scalable architectures capable of processing multiple customer interaction data streams
- Collaborating with other scientists and technical teams to implement production systems that can process complex customer journey data
- Leading research initiatives to resolve scientific ambiguities in applying ML methods to causal inference problems
- Presenting findings to stakeholders and contributing to Amazons research paradigms
The ideal candidate will have:
- Deep expertise in causal inference and machine learning
- Experience with large-scale data processing and modeling
- Strong research background in econometrics or related fields
- Ability to bridge theoretical foundations with practical implementations
- Excellence in communicating complex technical concepts to diverse audiences
Your work will directly impact critical business decisions across Amazons retail business helping optimize the balance between inventory costs and customer experience while contributing to scientific developments in the intersection of machine learning and causal inference.
- 2 years of building models for business application experience
- PhD or Masters degree and 2 years of CS CE ML or related field experience
- Experience programming in Java C Python or related language
- Experience in any of the following areas: algorithms and data structures parsing numerical optimization data mining parallel and distributed computing high-performance computing
- Experience using Unix/Linux
- Experience in professional software development
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 for more information. If the country/region youre applying in isnt 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 $136000/year in our lowest geographic market up to $223400/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 This position will remain posted until filled. Applicants should apply via our internal or external career site.
Employment Type
Full-Time
Key Skills
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