Risk Manager III - Amz19105.3

Amazon Amazon · Big Tech · Chicago, IL · Corporate Operations

This role focuses on managing risks associated with AI and machine learning models and processes, ensuring compliance with regulatory requirements and internal standards. It involves working with stakeholders to identify risks, manage use cases, maintain inventories, and provide training on AI/ML risk management.

What you'd actually do

  1. Support the execution of governance and compliance activities for AI and machine learning (ML) risk models.
  2. Assist in managing AI/ML risk management processes in alignment with regulatory requirements.
  3. Work with stakeholders and team members to ensure requisite activities associated with AI/ML regulatory guidance occur.
  4. Work with key stakeholders to ensure requisite activities within the enterprise AI/ML Risk Management Standard occur.
  5. Work with key stakeholders on identifying heightened risks, controls, and value of prospective Al/ML use cases.

Skills

Required

  • program, project or risk management
  • owning program strategy, end to end delivery, and communication results to leadership
  • using data and metrics to determine and drive improvements
  • governance and compliance activities for AI and machine learning (ML) risk models
  • AI/ML risk management processes
  • regulatory requirements
  • enterprise AI/ML Risk Management Standard
  • identifying heightened risks, controls, and value of prospective Al/ML use cases
  • Al/ML use intake process
  • inventory of Al/ML use cases
  • review and approval
  • effective challenge of new Al/ML use cases
  • execution of requisite control activities
  • enterprise Al/ML strategy
  • develop and deliver training content and socialization about AI/ML risk processes and controls

Nice to have

  • Master’s degree or foreign equivalent degree in Business Administration, Risk Management, Operations Research or related field

What the JD emphasized

  • AI and machine learning (ML) risk models
  • AI/ML risk management processes
  • AI/ML regulatory guidance
  • enterprise AI/ML Risk Management Standard
  • heightened risks, controls, and value of prospective Al/ML use cases
  • comprehensive Al/ML use intake process
  • inventory of Al/ML use cases
  • review and approval
  • effective challenge
  • enterprise Al/ML strategy
  • training content and socialization about AI/ML risk processes and controls