Machine Learning Applied Scientist, Buyer Risk Prevention

$136,000 - $222,200/Yr

Amazon - San Diego, CA

Full-time - Senior

San Diego, CA

10,001+ employees

Sporting Goods, Hobby, Musical Instrument, Book, and Miscellaneous Retailers

About the position

The Machine Learning Applied Scientist position at Amazon focuses on utilizing machine learning and statistical techniques to enhance customer safety by preventing unauthorized access to accounts. The role involves building advanced algorithmic systems to manage trust and safety for millions of customers, analyzing large datasets, and developing state-of-the-art algorithms to address real-world challenges. The Amazon Account Integrity team is dedicated to protecting customer trust while ensuring fair treatment of all users.

Responsibilities

• Develop and implement machine learning models to identify and mitigate risks associated with customer accounts.
• Analyze and model large datasets to create algorithms that solve real-world problems.
• Collaborate with team members to iterate on machine learning risk models and enforcement policies.
• Communicate findings and present data effectively to stakeholders.
• Continuously innovate and simplify processes to enhance customer safety.

Requirements

• PhD in Computer Science, Computer Engineering, or a related field, or a Master's degree with 4+ years of relevant experience.
• 3+ years of experience in building machine learning models or developing algorithms for business applications.
• Strong programming skills in Java, C++, Python, or similar languages.
• Experience in algorithms and data structures, numerical optimization, and data mining.
• Excellent communication and data presentation skills.

Nice-to-haves

• Publications in top-tier conferences such as CVPR, ICCV, ECCV, or NeurIPS.
• Experience in deep learning, computer vision, or human-robot interaction.

Benefits

• Competitive salary ranging from $136,000 to $222,200 based on experience and location.
• Equity and sign-on payments as part of total compensation.
• Comprehensive medical, financial, and other benefits.