Job summary
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 preventing eCommerce abuse?

Are you excited by the prospect of analyzing and modeling terabytes of data and creating state-of-the-art algorithms to solve real world problems?

Do you like to own end-to-end business problems/metrics and directly impact the profitability of the company? Do you enjoy collaborating in a diverse team environment?

If yes, then you may be a great fit to join the Amazon Buyer Risk Prevention (BRP) Machine Learning group. We are looking for a talented scientist who is passionate to build advanced algorithmic systems that help manage safety of millions of transactions every day.

Major responsibilities

• Use statistical and machine learning techniques to create scalable risk management systems
• Learning and understanding large amounts of Amazon’s historical business data for specific instances of risk or broader risk trends
• Design, development and evaluation of highly innovative models for risk management
• Working closely with software engineering teams to drive real-time model implementations and new feature creations
• Working closely with operations staff to optimize risk management operations,
• Establishing scalable, efficient, automated processes for large scale data analyses, model development, model validation and model implementation
• Tracking general business activity and providing clear, compelling management reporting on a regular basis
• Research and implement novel machine learning and statistical approaches

BASIC QUALIFICATIONS

• PhD or equivalent Master's Degree plus 4+ years of experience in CS, CE, ML or related field
• 2+ years of experience of building machine learning models for business application
• Experience programming in Java, C++, Python or related language

PREFERRED QUALIFICATIONS

• A PhD in CS, Machine Learning, Statistics, Operations Research or relevant field
• 5+ years of industry experience in predictive modeling and analysis
• Strong Machine Learning breadth and depth
• Strong skills with SQL
• Strong skills with Spark/Python/Perl (or similar)
• Ability to think creatively and solve problems
• Good written and spoken communication skills
• Demonstrated track record of cultivating strong working relationships and driving collaboration across multiple technical and business teams