Principal Applied Scientist, Amazon Stores Economics & Science (SEAS)
Job Description
Stores Economics and Science (SEAS) is an interdisciplinary science and engineering team in Amazon's Stores organization with a peak-jumping mission: we apply expertise in science and engineering to move from local to global optima in methods, models, and software. We pursue this mission by leveraging frontier science; collaborating with partner teams; and learning from the tools, experience, and perspective of others. We scale by solving problems, first in the small to prove concepts, and then in the large by building scalable solutions. We also help other teams within Amazon scale by hiring and developing the best and embedding them in other business units. In 2024, we are focused on economics and science in areas related to (1) improving delivery speed and lowering cost-to-serve, (2) seller fees and incentives, and (3) emerging machine learning using LLMs. We also have some ongoing and highly leveraged collaborations that help partner teams inside Amazon short-circuit months of R&D or otherwise look around corners. We are looking for a seasoned Applied Science leader to build and deliver cutting-edge science and engineering solutions to improve our Stores business. In this role, you will lead a team of scientists and engineers with backgrounds in machine learning, NLP, IR, statistics, and economics to identify bottlenecks in our business, conceive new ideas to overcome those challenges, and deploy scientific solutions in partnership with product teams. Your responsibilities include developing the scientific models, benchmarks, and services. Graduate education and hands-on experience in machine learning, optimization, causal inference, Bayesian statistics, deep learning, or other quantitative scientific fields is a must. To be successful in this role, you should be a quick learner and comfortable with a high degree of ambiguity.Key job responsibilitiesKnowledge of causal inference and forecasting models are preferred. Practical knowledge of how we can leverage Transformers, LLMs, or other deep learning techniques for a variety of applications is a must.
Locations
- United States, WA, Seattle, Seattle, WA, United States
- United States, CA, Palo Alto, Palo Alto, CA, United States
Salary
Salary not disclosed
Estimated Salary Rangehigh confidence
250,000 - 400,000 USD / yearly
Source: ai estimated
* This is an estimated range based on market data and may vary based on experience and qualifications.
Skills Required
- 10+ years of building machine learning models for business application experienceintermediate
- PhD, or Master's degree and 10+ years of applied research experienceintermediate
- Experience programming in Java, C++, Python or related languageintermediate
- Experience with neural deep learning methods and machine learningintermediate
Required Qualifications
- 10+ years of building machine learning models for business application experience (experience, 10 years)
- PhD, or Master's degree and 10+ years of applied research experience (experience, 10 years)
- Experience programming in Java, C++, Python or related language (experience)
- Experience with neural deep learning methods and machine learning (experience)
Preferred Qualifications
- Experience with modeling tools such as R, scikit-learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy etc. (experience)
- Experience with large scale distributed systems such as Hadoop, Spark etc. (experience)
- Los Angeles County applicants: Job duties for this position include: work safely and cooperatively with other employees, supervisors, and staff; adhere to standards of excellence despite stressful conditions; communicate effectively and respectfully with employees, supervisors, and staff to ensure exceptional customer service; and follow all federal, state, and local laws and Company policies. Criminal history may have a direct, adverse, and negative relationship with some of the material job duties of this position. These include the duties and responsibilities listed above, as well as the abilities to adhere to company policies, exercise sound judgment, effectively manage stress and work safely and respectfully with others, exhibit trustworthiness and professionalism, and safeguard business operations and the Company’s reputation. Pursuant to the Los Angeles County Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records. (experience)
- Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $179,000/year in our lowest geographic market up to $309,400/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
- Knowledge of causal inference and forecasting models are preferred. Practical knowledge of how we can leverage Transformers, LLMs, or other deep learning techniques for a variety of applications is a must.
Documents
Tags & Categories
Principal Applied Scientist, Amazon Stores Economics & Science (SEAS)
Job Description
Stores Economics and Science (SEAS) is an interdisciplinary science and engineering team in Amazon's Stores organization with a peak-jumping mission: we apply expertise in science and engineering to move from local to global optima in methods, models, and software. We pursue this mission by leveraging frontier science; collaborating with partner teams; and learning from the tools, experience, and perspective of others. We scale by solving problems, first in the small to prove concepts, and then in the large by building scalable solutions. We also help other teams within Amazon scale by hiring and developing the best and embedding them in other business units. In 2024, we are focused on economics and science in areas related to (1) improving delivery speed and lowering cost-to-serve, (2) seller fees and incentives, and (3) emerging machine learning using LLMs. We also have some ongoing and highly leveraged collaborations that help partner teams inside Amazon short-circuit months of R&D or otherwise look around corners. We are looking for a seasoned Applied Science leader to build and deliver cutting-edge science and engineering solutions to improve our Stores business. In this role, you will lead a team of scientists and engineers with backgrounds in machine learning, NLP, IR, statistics, and economics to identify bottlenecks in our business, conceive new ideas to overcome those challenges, and deploy scientific solutions in partnership with product teams. Your responsibilities include developing the scientific models, benchmarks, and services. Graduate education and hands-on experience in machine learning, optimization, causal inference, Bayesian statistics, deep learning, or other quantitative scientific fields is a must. To be successful in this role, you should be a quick learner and comfortable with a high degree of ambiguity.Key job responsibilitiesKnowledge of causal inference and forecasting models are preferred. Practical knowledge of how we can leverage Transformers, LLMs, or other deep learning techniques for a variety of applications is a must.
Locations
- United States, WA, Seattle, Seattle, WA, United States
- United States, CA, Palo Alto, Palo Alto, CA, United States
Salary
Salary not disclosed
Estimated Salary Rangehigh confidence
250,000 - 400,000 USD / yearly
Source: ai estimated
* This is an estimated range based on market data and may vary based on experience and qualifications.
Skills Required
- 10+ years of building machine learning models for business application experienceintermediate
- PhD, or Master's degree and 10+ years of applied research experienceintermediate
- Experience programming in Java, C++, Python or related languageintermediate
- Experience with neural deep learning methods and machine learningintermediate
Required Qualifications
- 10+ years of building machine learning models for business application experience (experience, 10 years)
- PhD, or Master's degree and 10+ years of applied research experience (experience, 10 years)
- Experience programming in Java, C++, Python or related language (experience)
- Experience with neural deep learning methods and machine learning (experience)
Preferred Qualifications
- Experience with modeling tools such as R, scikit-learn, Spark MLLib, MxNet, Tensorflow, numpy, scipy etc. (experience)
- Experience with large scale distributed systems such as Hadoop, Spark etc. (experience)
- Los Angeles County applicants: Job duties for this position include: work safely and cooperatively with other employees, supervisors, and staff; adhere to standards of excellence despite stressful conditions; communicate effectively and respectfully with employees, supervisors, and staff to ensure exceptional customer service; and follow all federal, state, and local laws and Company policies. Criminal history may have a direct, adverse, and negative relationship with some of the material job duties of this position. These include the duties and responsibilities listed above, as well as the abilities to adhere to company policies, exercise sound judgment, effectively manage stress and work safely and respectfully with others, exhibit trustworthiness and professionalism, and safeguard business operations and the Company’s reputation. Pursuant to the Los Angeles County Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records. (experience)
- Our compensation reflects the cost of labor across several US geographic markets. The base pay for this position ranges from $179,000/year in our lowest geographic market up to $309,400/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
- Knowledge of causal inference and forecasting models are preferred. Practical knowledge of how we can leverage Transformers, LLMs, or other deep learning techniques for a variety of applications is a must.