Mistral AISingapore
AmazonPosted 2d ago
L3
Risk Manager (2LoD, Model Risk Validation), Risk and Compliance Solutions
Risk Manager (2LoD, Model Risk Validation), Risk and Compliance Solutions at Amazon scores 65 out of 100 on AI centrality, which makes it a Level 3 role on this board.
CO, Bogotamidfull-time
AI in this role
Risk Manager specializing in independent AI and machine learning model risk validation and governance.
model-risk-managementmodel-validationai-governancecompliancerisk-assessment
Key job responsibilities
• Drive vision and execution of tactical elements of governance and compliance activities for AI and machine learning (ML) risk models.
• Assist in managing AI/ML risk management processes in alignment with regulatory requirements.
• Work with stakeholders and team members to ensure requisite activities associated with AI/ML regulatory guidance occur.
• Work with team members and leadership to prepare content and facilitate key stakeholder and working group meetings.
• Work with key stakeholders to ensure requisite activities within the enterprise AI/ML Risk Management Standard occur
• Work with key stakeholders on identifying heightened risks, controls, and value of prospective Al/ML use cases.
• Work with Enterprise Architecture and data scientists to create and sustain a comprehensive Al/ML use intake process.
• Maintain the comprehensive inventory of Al/ML use cases, evidence of review and approval, and associated documentation.
• Partner with other functions (e.g., Legal, Compliance) on requisite review and effective challenge of new Al/ML use cases.
• Partner with subject-matter-experts and strategic leaders to ensure execution of requisite control activities as articulated in the enterprise Al/ML strategy.
• Work with internal stakeholders to develop and deliver training content and socialization about AI/ML risk processes and controls
A day in the life
You will serve as the primary subject matter expert for creating and overseeing the model risk management policy, independent governance of model risk, and validating and performing model validation. Your role will include working with the operations teams and Boards to drive models that effectively mitigate the risks to our sellers and buyers and meet regulatory requirements and mitigate financial crime, operational, financial, strategic, and customer risk. As you do this, you'll be working within a global team of risk and compliance 2LoD Amazonians across the globe.
About the team
Diverse Experiences: AWS values diverse experiences. Even if you do not meet all of the preferred qualifications and skills listed in the job below, we encourage candidates to apply. If your career is just starting, hasn’t followed a traditional path, or includes alternative experiences, don’t let it stop you from applying.
Why AWS? Amazon Web Services (AWS) is the world’s most comprehensive and broadly adopted cloud platform. We pioneered cloud computing and never stopped innovating — that’s why customers from the most successful startups to Global 500 companies trust our robust suite of products and services to power their businesses.
Inclusive Team Culture - Here at AWS, it’s in our nature to learn and be curious. Our employee-led affinity groups foster a culture of inclusion that empower us to be proud of our differences. Ongoing events and learning experiences, including our Conversations on Race and Ethnicity (CORE) and AmazeCon (diversity) conferences, inspire us to never stop embracing our uniqueness.
Mentorship & Career Growth - We’re continuously raising our performance bar as we strive to become Earth’s Best Employer. That’s why you’ll find endless knowledge-sharing, mentorship and other career-advancing resources here to help you develop into a better-rounded professional.
Work/Life Balance - We value work-life harmony. Achieving success at work should never come at the expense of sacrifices at home, which is why we strive for flexibility as part of our working culture. When we feel supported in the workplace and at home, there’s nothing we can’t achieve in the cloud.
Basic qualifications
- Bachelor's degree, or Bachelor's degree in BI, finance, engineering, statistics, computer science, mathematics, finance or equivalent quantitative field
- 4+ years of working with or evaluating AI systems experience
- 3+ Experience in internal audit and risk management or equivalent
- Experience in English-language communication skills, both written and verbal
- Experience communicating to senior management and customers verbally and in writing
Preferred qualifications
- Master's degree
- Experience in processing data with a massively parallel technology (such as Redshift, Teradata, Netezza, Spark or Hadoop based big data solution)
Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how-we-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.
Prepare for this job
A free preview built only from this posting: what it asks for, what you could be asked in an interview, and how to adjust your resume.
Skills and AI tools this role asks for
Model Risk ManagementModel ValidationAI GovernanceComplianceRisk Assessment
Questions you could be asked
- Tell me about a project where model risk management was part of your work. What did you do?
- Tell me about a project where model validation was part of your work. What did you do?
- Tell me about a project where ai governance was part of your work. What did you do?
- Tell me about a project where compliance was part of your work. What did you do?
- Tell me about a project where risk assessment was part of your work. What did you do?
Adapt your resume
- List these exact terms on your resume: Model Risk Management, Model Validation, AI Governance, Compliance, and Risk Assessment. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them — a tool named with nothing behind it rarely survives a human read.
- Show where AI is part of your daily process, not a one-off project — this role expects it to be a running habit.
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