ML Applied Scientist

Job ID: 1399327 | Services LLC


Do you want to join an innovative team of scientists who use machine learning and statistical techniques to help Amazon provide the best customer experience by protecting Amazon customers from hackers and bad actors? Do you want to build advanced algorithmic systems that help manage the trust and safety of millions of customer every day? Are you excited by the prospect of analyzing and modeling terabytes of data and create state-of-art algorithms to solve real world problems? Do you like to innovate and simplify? If yes, then you may be a great fit to join the Amazon Account Integrity team.

The Amazon Account Integrity team works to ensure that customers are protected from bad actors trying to access their accounts. Our greatest challenge is protecting customer trust without unjustly harming good customers. To strike the right balance, we invest in mechanisms which allow us to accurately identify and mitigate risk, and to quickly correct and learn from our mistakes. This strategy includes continuously evolving enforcement policies, iterating our Machine Learning risk models, and exercising high‐judgement decision‐making where we cannot apply automation.

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· A MS in CS machine learning, Statistics or in a highly quantitative field
· 3+ years of hands-on experience in predictive modeling and large data analysis
· Communication and data presentation skills
· Problem solving ability


· A PhD in CS machine learning, Statistics or in a highly quantitative field
· 5+ years of industry experience in predictive modeling and large data analysis
· Strong skills with Python/Spark (or similar scripting language), Java/C++ and SQL
· Strong problem solving and dive deep ability
· Strong communication, writing and data presentation skills

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