Risk Analyst Ii, Payment Risk Machine Learning
- San José
- Permanente
- Tiempo completo
- Bachelor's degree or equivalent
- Experience handling confidential information
Have you ever thought about what it takes to detect and prevent fraudulent activity in hundreds of millions of eCommerce transactions across the globe?
What would you do to increase trust in an online marketplace where millions of buyers and sellers transact?
How would you build systems that evolve over time to proactively identify and neutralize new and emerging fraud threats?
The Risk Analyst II in Machine Learning Insights (MLI) team is responsible for providing support to Payment Risk ML team.
This includes using analytical and business skills to perform ML Model evaluation related deep dives, educating partners on model actions, providing support in UAT, monitoring alerts and much more.
Key job responsibilities
A day in the life
- Provide time sensitive analytics to partner teams
- Deep Dive on ML model decisions using SQL
- Identify root cause and work with partners such as ML teams to develop sustainable solutions
- Automate tasks using dashboards
About the team
Our Risk Analytics team plays a vital role by translating complex requirements into scalable and standardized processes.
As a Risk Analyst, you will collaborate closely with our talented Applied Scientists to bridge gaps, drive efficiency, and enable speed through standardization and automation.
Your work will directly impact our customers by through our mission of making Amazon the safest place to transact online.
On this team, you'll have the opportunity to tackle challenging problems, learn from experienced professionals, and grow your skills in a supportive environment.
We value transparency, inclusivity, and continuous improvement
Calle Blancos, C, CRI | San Jose, CRI | San Jose, SJ, CRI
- 3+ years of compliance program management, legal, governance, audit, risk/loss prevention, or equivalent experience
- Professional auditing qualification, or similar risk or compliance credentials
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