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AI/ML Governance and Model Risk Management |

AI/ML Governance and Model Risk Management |

manpower staffing services (singapore) pte ltd
2-5 Years
SGD 1.2 - 1.44 LPA
  • Posted a day ago
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Job Description

Key Responsibilities

  • Support the governance and oversight of Machine Learning (ML) and Generative AI (GenAI) models to ensure compliance with internal policies, regulatory requirements, and industry best practices.
  • Manage the end-to-end model lifecycle, including model identification, development, validation, approval, deployment, ongoing monitoring, periodic reviews, and model retirement.
  • Maintain and update model inventories, governance documentation, policy documents, and model risk records to ensure accuracy and alignment with regulatory requirements and internal standards.
  • Monitor compliance with enterprise model risk management frameworks, banking regulations, and internal governance policies.
  • Prepare and communicate model compliance reports, risk assessments, and presentations for model owners, senior management, internal auditors, and regulators.
  • Coordinate remediation plans, corrective actions, and training initiatives arising from regulatory reviews, audit findings, or model validation outcomes.
  • Partner closely with Data Science, Engineering, and Model Risk Management teams to ensure models are developed, validated, deployed, and monitored in accordance with established governance standards and validation requirements.
  • Coordinate activities across the AI/ML lifecycle, managing project dependencies, technical considerations, and delivery milestones to support responsible AI implementation.
  • Ensure AI models remain auditable, transparent, and compliant by maintaining complete governance documentation and supporting regulatory and audit readiness.
  • Support the continuous enhancement of model governance frameworks, policies, controls, and documentation to strengthen enterprise AI risk management practices.
  • Stay informed of emerging AI governance regulations, industry standards, and best practices, recommending improvements where appropriate.


Requirements

  • Bachelor's Degree in Finance, Risk Management, Computer Science, Data Science, Information Technology, Mathematics, Statistics, or a related discipline.
  • Minimum 2 years of experience in Model Risk Management, Model Validation, AI Governance, Risk Management, Regulatory Compliance, or a related function within the banking or financial services industry.
  • Working knowledge of Machine Learning (ML) and Generative AI (GenAI) models and an understanding of their development lifecycle, governance, and associated risks.
  • Understanding of enterprise model risk management frameworks, model validation methodologies, and regulatory expectations for AI and analytical models.
  • Experience preparing governance documentation, maintaining model inventories, supporting audits, and coordinating regulatory compliance activities.
  • Excellent analytical, problem-solving, organisational, and stakeholder management skills.
  • Excellent written and verbal communication skills, with the ability to present information effectively to both technical and non-technical stakeholders.
  • Ability to work collaboratively with cross-functional teams, including Data Science, Engineering, Risk, Compliance, and Audit.
  • Familiarity with regulatory frameworks and industry standards such as the Monetary Authority of Singapore (MAS) guidelines, National Institute of Standards and Technology (NIST) Artificial Intelligence Risk Management Framework (AI RMF), or similar governance frameworks.
  • Professional certifications such as Project Management Professional (PMP), Financial Risk Manager (FRM), Professional Risk Manager (PRM), Certified in Risk and Information Systems Control (CRISC), or NIST AI Risk Management Framework (AI RMF) certifications would be good to have.

Jireli Gem Mejia Cabria EA License No.: 02C3423 Personnel Registration No.: R1434374

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More Info

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Key Skills

Industry Standards

Regulatory Frameworks

Model Risk Management

Model Inventories

Governance Documentation

Enterprise Model Risk Management Frameworks

Model Validation Methodologies

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