At Amazon, we strive every day to be Earth’s most customer centric company. Amazon Perfect Order Experience (POE) team works to ensure that customers can buy with confidence on Amazon. We develop and implement large scale machine learning solutions to protect the buying experience on Amazon while minimizing friction for our selling partners. We develop state-of-the art Natural Language Processing models to detect negative customer experience in real-time and build an ever-evolving risk monitoring system to proactive protect customer trust.
We are looking for an Applied Scientist to build efficient and scalable machine learning systems to keep amazon the safest and most trusted place to shop online. In this role, you will work closely with scientists, economists and engineers to build end-to-end ML solutions that have immediate impacts on amazon customers. You will work on a variety of research areas including:
· Develop NLP and deep learning models to extract insights from customer feedback.
· Build the next generation of risk monitoring system using predictive modeling, graph mining and unsupervised learning techniques.
· Apply the state-of-the art Computer Vision technique to develop a highly scalable ML solution for product authentication.
· Develop and deploy real-time ML models using AWS services.
Please visit https://www.amazon.science for more information
· Master's degree in Computer Science, Statistics, Applied Math, Operations Research, Economics, or a related quantitative field.
· Hands-on experience in developing machine learning models using Python, R, Java or other programming languages.
· 3+ years of relevant ML research experience in industry and/or academia.
· Ability to self-direct, multitask, and prioritize a constantly evolving workload.
PhD in Computer Science, Statistics, Applied Math, Operations Research, Economics, or a related quantitative field with at least 2 years of working experience as Data/Research/Applied Scientist.
· Extensive knowledge and practical experience in statistics, machine learning, or deep learning.
· Extensive experience applying theoretical models in an applied environment.
· Excellent oral and written communication skills including the ability to communicate effectively with both technical and non-technical stakeholders.
Amazon is committed to a diverse and inclusive workplace. Amazon is an equal opportunity employer and does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status. For individuals with disabilities who would like to request an accommodation, please visit https://www.amazon.jobs/en/disability/us