Data Engineering- Compromise & Fraud Prevention
Tasks
- Build and leverage reputation models
- Collaborate with teams across Microsoft
- Conduct design reviews and system architecture planning
- Debug production issues and mitigate impact
- Deliver features for fraud detection and blocking
- Design and develop distributed software services
- Develop modular, secure, reliable services
- Engage with customer and partner needs
- Follow modern software engineering practices
- Implement data-driven solutions
- Improve test coverage and integration tests
- Integrate machine learning models for real-time abuse detection
- Maintain and scale data tools for transformation and access
- Troubleshoot and optimize automation and monitoring
Perks/Benefits
Skills/Tech-stack
Automation | Data Engineering | Data Modeling | Data Transformation | Debugging | Distributed Systems | Machine Learning | Scalability | Security and Compliance | Service Development | Software Engineering | System design | Telemetry Analysis | Telemetry Monitoring
Education
Roles
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