Amazon
Applied Scientist, FinAuto
- Eligibility
- Not stated
- Batch
- Not stated
- Experience
- Not stated
- Salary
- Not stated
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About this role
About the role: - Build machine learning systems to detect and prevent fraudulent, abusive and wasteful financial transactions at scale - Work on financial systems processing billions of dollars in transactions daily across Amazon's operations - Research and deploy novel approaches to identify anomalies, theft, fraud and abuse in transaction data What you'll do: - Analyze large volumes of Amazon's historical transaction data to extract insights and automate key processes - Develop machine learning and statistical models for detecting fraudulent and abusive transactions - Create scalable solutions using data mining, statistical analysis and machine learning techniques - Partner with engineering and business teams to put models into production - Mentor other scientists and engineers on machine learning applications - Identify new opportunities where machine learning can solve business problems What they're looking for: - Programming experience in Java, C++, Python or related languages - SQL and RDBMS experience (e.g., Oracle) or data warehouse knowledge Good to know: - Experience implementing algorithms with both existing toolkits and custom code is preferred - Publications at top-tier peer-reviewed conferences or journals is a plus