Applied Scientist II, Global Trade
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Monthly Salary:
Posted on:
Yesterday
Vacancies:
1 Vacancy
Job Summary
This role is to solve business problems in Machine Learning for the Seller and Fulfilment Tech (SFT) org.
The overarching goal of the team is to enhance ML expertise and fluency within SFT and across IST championing engineering and operational excellence in ML model development and other related parts of the ML model lifecycle. Some of the key areas which the team owns in this space area:
Selection Recommendations Registration improvements Bad actor detection and prevention
Selection economics Inventory recommendation Delivery Promise Predictions Seller success.
Within the ML space the scientist would have to solve intrinsically hard problems where neither problem nor solution is well defined. So the leader should have high focus on building a deep understanding of the ML science space experimentation methodology as well as a high focus on embracing external trends especially applications of GenerativeAI and LLMs.
A large focus area for the role is to also contribute towards the science and research aspects. This role applies and extends existing scientific techniques and invents new ones to address specific customers needs or business problems at a project level. This should also lead to regular contributions to internal or external peer-reviewed publications that validate novelty
- 3 years of building models for business application experience
- PhD or Masters degree and 4 years of CS CE ML or related field experience
- Experience in patents or publications at top-tier peer-reviewed conferences or journals
- 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
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.
The overarching goal of the team is to enhance ML expertise and fluency within SFT and across IST championing engineering and operational excellence in ML model development and other related parts of the ML model lifecycle. Some of the key areas which the team owns in this space area:
Selection Recommendations Registration improvements Bad actor detection and prevention
Selection economics Inventory recommendation Delivery Promise Predictions Seller success.
Within the ML space the scientist would have to solve intrinsically hard problems where neither problem nor solution is well defined. So the leader should have high focus on building a deep understanding of the ML science space experimentation methodology as well as a high focus on embracing external trends especially applications of GenerativeAI and LLMs.
A large focus area for the role is to also contribute towards the science and research aspects. This role applies and extends existing scientific techniques and invents new ones to address specific customers needs or business problems at a project level. This should also lead to regular contributions to internal or external peer-reviewed publications that validate novelty
- 3 years of building models for business application experience
- PhD or Masters degree and 4 years of CS CE ML or related field experience
- Experience in patents or publications at top-tier peer-reviewed conferences or journals
- 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
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.
Required Experience:
IC
Key Skills
- Laboratory Experience
- Immunoassays
- Machine Learning
- Biochemistry
- Assays
- Research Experience
- Spectroscopy
- Research & Development
- cGMP
- Cell Culture
- Molecular Biology
- Data Analysis Skills
About Company
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