At Amazon, we strive every day to be Earth’s most customer centric company. Do you want to join an innovative team who uses machine learning, statistical and advanced analytical techniques to keep Amazon the safest and most trusted place to shop online? Are you interested in guiding key business decisions that help manage the trust and safety of millions of products and transactions every day?
Amazon perfect order experience team is looking for an Applied Scientist to build efficient, flexible, and scalable analytics and machine learning solutions. In this role, you will have the end-to-end ownership of ML applications. You will work closely with brilliant scientists, economists and engineers in the team to build ML models, engineering pipelines and science applications, which have direct impacts on Amazon's Customers and Selling Partners. You will play an important role in leading the science innovation and contributing to critical design decisions. You will apply techniques such as graph modeling, natural language processing, and deep learning to ensure that Customers receive authentic products in the condition and with the functionality they expect, and quickly making things right when they don’t.
· Master's degree in Computer Science, Statistics, Applied Math, Operations Research, Economics, or a related quantitative field.
· Hands on experience with an object oriented language such as Python, C++ or Java, and a scripting language (like R) for data analytics and ML model development.
· Hands on experience with statistical analysis, applying various machine learning techniques including supervised/un-supervised learning.
· 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 5 years of working experience as Data Scientist.
· Hands on experience in NLP and active learning.
· Track record for being detail-oriented with a demonstrated ability to self-motivate and follow-through on projects
· Excellent oral and written communication skills including the ability to communicate effectively with both technical and non-technical stakeholders.
· Experience of leading science projects and deal with ambiguities.