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Job Description
Structured overview of role & requirementsAbout This Role
Lead research and development of machine learning and statistical methods to detect anomaly, theft, fraud, abuse, and waste in financial transactions.
Analyze large volumes of Amazon's historical transaction data to build scalable solutions and automate key financial processes.
Collaborate with developers and business teams to deploy models into production and mentor other scientists and engineers in ML techniques.
Minimum Requirements
Programming experience in Java, C++, Python or related languages.
Experience with SQL and Relational Database Management Systems (e.g., Oracle) or Data Warehouse.
Work Experience Required: Not explicitly mentioned in the JD.
Preferred experience includes implementing algorithms with toolkits and custom code; publications in top-tier peer-reviewed conferences or journals are a plus but not mandatory.
Ideal Candidate Profile
Experienced in applied machine learning and statistical analysis in financial transaction data or related domains involving large-scale data processing.
Able to drive end-to-end machine learning projects from research through production deployment in a distributed cloud environment.
Skilled in collaborating cross-functionally with engineering and business teams to identify and solve complex fraud, theft, and waste detection problems at scale.