Applied Scientist II, Amazon Selling Partner Trust & Store Integrity Science
Job Description
Are you passionate about applying machine learning and advanced statistical techniques at the scale of one of the world's larges product catalogs? Do you want to be at the forefront of developing innovative solutions that safeguard Amazon's product catalog while empowering millions of Selling Partners to thrive? Do you thrive in a collaborative environment where diverse perspectives drive breakthrough solutions?If yes, we invite you to join the Amazon Risk Intelligence Science Team. We're seeking an exceptional scientist who can revolutionize how we protect our marketplace through intelligent automation. As a key member of our team, you'll develop and deploy state-of-the-art machine learning systems that analyze millions of product listings daily, ensuring the integrity and trustworthiness of Amazon's catalog while scaling our operations to new heights. Your work will directly impact the quality of the shopping experience for hundreds of millions of customers worldwide.Key job responsibilitiesUse machine learning and statistical techniques to create scalable catalog abuse detection solutions that identify listing violations, selling partner integrity, and content manipulationInnovate with the latest GenAI technology to build highly automated solutions for efficient catalog monitoring, content verification, and automated listing complianceDesign, develop and deploy end-to-end machine learning solutions in the Amazon production environmentLearn, explore and experiment with the latest machine learning advancements to protect selling partner trust and integrityA day in the lifeYou'll be working closely with business partners and engineering teams to create end-to-end scalable machine learning solutions that address real-world problems. You will build scalable, efficient, and automated processes for large-scale data analyses, model development, model validation, and model implementation.You will also be providing clear and compelling reports for your solutions and contributing to the ongoing innovation and knowledge-sharing that are central to the team's success.
Locations
- United States, WA, Seattle, Seattle, WA, United States
Salary
Salary not disclosed
Estimated Salary Rangehigh confidence
180,000 - 250,000 USD / yearly
Source: ai estimated
* This is an estimated range based on market data and may vary based on experience and qualifications.
Skills Required
- - PhD, or Master's degree and 3+ years of CS, CE, ML or related field experienceintermediate
- - 3+ years of building machine learning models or developing algorithms for business application experienceintermediate
- - Experience programming in Java, C++, Python or related languageintermediate
- - Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computingintermediate
Required Qualifications
- - PhD, or Master's degree and 3+ years of CS, CE, ML or related field experience (experience, 3 years)
- - 3+ years of building machine learning models or developing algorithms for business application experience (experience, 3 years)
- - Experience programming in Java, C++, Python or related language (experience)
- - Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing (experience)
Preferred Qualifications
- - Experience with generative deep learning models applicable to the creation of synthetic humans like CNNs, GANs, VAEs and NF (experience)
- - Experience in patents or publications at top-tier peer-reviewed conferences or journals (experience)
- Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $136,000/year in our lowest geographic market up to $223,400/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. (experience)
Responsibilities
- Use machine learning and statistical techniques to create scalable catalog abuse detection solutions that identify listing violations, selling partner integrity, and content manipulation
- Innovate with the latest GenAI technology to build highly automated solutions for efficient catalog monitoring, content verification, and automated listing compliance
- Design, develop and deploy end-to-end machine learning solutions in the Amazon production environment
- Learn, explore and experiment with the latest machine learning advancements to protect selling partner trust and integrity
Documents
Tags & Categories
Applied Scientist II, Amazon Selling Partner Trust & Store Integrity Science
Job Description
Are you passionate about applying machine learning and advanced statistical techniques at the scale of one of the world's larges product catalogs? Do you want to be at the forefront of developing innovative solutions that safeguard Amazon's product catalog while empowering millions of Selling Partners to thrive? Do you thrive in a collaborative environment where diverse perspectives drive breakthrough solutions?If yes, we invite you to join the Amazon Risk Intelligence Science Team. We're seeking an exceptional scientist who can revolutionize how we protect our marketplace through intelligent automation. As a key member of our team, you'll develop and deploy state-of-the-art machine learning systems that analyze millions of product listings daily, ensuring the integrity and trustworthiness of Amazon's catalog while scaling our operations to new heights. Your work will directly impact the quality of the shopping experience for hundreds of millions of customers worldwide.Key job responsibilitiesUse machine learning and statistical techniques to create scalable catalog abuse detection solutions that identify listing violations, selling partner integrity, and content manipulationInnovate with the latest GenAI technology to build highly automated solutions for efficient catalog monitoring, content verification, and automated listing complianceDesign, develop and deploy end-to-end machine learning solutions in the Amazon production environmentLearn, explore and experiment with the latest machine learning advancements to protect selling partner trust and integrityA day in the lifeYou'll be working closely with business partners and engineering teams to create end-to-end scalable machine learning solutions that address real-world problems. You will build scalable, efficient, and automated processes for large-scale data analyses, model development, model validation, and model implementation.You will also be providing clear and compelling reports for your solutions and contributing to the ongoing innovation and knowledge-sharing that are central to the team's success.
Locations
- United States, WA, Seattle, Seattle, WA, United States
Salary
Salary not disclosed
Estimated Salary Rangehigh confidence
180,000 - 250,000 USD / yearly
Source: ai estimated
* This is an estimated range based on market data and may vary based on experience and qualifications.
Skills Required
- - PhD, or Master's degree and 3+ years of CS, CE, ML or related field experienceintermediate
- - 3+ years of building machine learning models or developing algorithms for business application experienceintermediate
- - Experience programming in Java, C++, Python or related languageintermediate
- - Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computingintermediate
Required Qualifications
- - PhD, or Master's degree and 3+ years of CS, CE, ML or related field experience (experience, 3 years)
- - 3+ years of building machine learning models or developing algorithms for business application experience (experience, 3 years)
- - Experience programming in Java, C++, Python or related language (experience)
- - Experience in any of the following areas: algorithms and data structures, parsing, numerical optimization, data mining, parallel and distributed computing, high-performance computing (experience)
Preferred Qualifications
- - Experience with generative deep learning models applicable to the creation of synthetic humans like CNNs, GANs, VAEs and NF (experience)
- - Experience in patents or publications at top-tier peer-reviewed conferences or journals (experience)
- Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $136,000/year in our lowest geographic market up to $223,400/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. (experience)
Responsibilities
- Use machine learning and statistical techniques to create scalable catalog abuse detection solutions that identify listing violations, selling partner integrity, and content manipulation
- Innovate with the latest GenAI technology to build highly automated solutions for efficient catalog monitoring, content verification, and automated listing compliance
- Design, develop and deploy end-to-end machine learning solutions in the Amazon production environment
- Learn, explore and experiment with the latest machine learning advancements to protect selling partner trust and integrity