AI Governance Manager

SCOR is strengthening its Group‑wide AI Governance capabilities to support the safe, ethical, compliant, and value‑driven use of Artificial Intelligence across internal operations and client‑facing solutions.

The AI Governance Manager / Senior Analyst will support the Lead Data & AI Governance in designing, maintaining, and operating SCOR’s AI Governance framework. The role covers regulatory readiness (notably the EU AI Act), governance standards and playbooks, AI risk management, and close collaboration with business, technology, data, risk, compliance, and legal teams across the Group.

This role sits at the intersection of AI, regulation, risk management, and enterprise governance, and requires both strong governance discipline and a solid technical understanding of modern AI systems.

Key duties and responsibilities

1. EU AI Act & Regulatory Readiness

• Support SCOR’s readiness for the EU AI Act and related AI regulations, including: 

  • Contribution to regulatory gap analyses and implementation plans
  • Alignment of governance processes, documentation, and controls with regulatory requirements
• Monitor regulatory developments related to AI (EU and international) and assess their impact on SCOR’s AI usage and AI solutions offered to clients, in coordination with Compliance and Legal teams. 
  
   

2. AI Governance Framework & Playbook

• Maintain and evolve the SCOR AI Playbook, ensuring alignment with: 

  • SCOR’s AI Strategy
  • Group policies, management standards, and ethical principles
• Contribute to defining and maintaining AI governance standards, guidance, templates, and control requirements covering: 
  • AI lifecycle management
  • Risk classification and documentation
  • Ethical, secure, and responsible AI use. 

3. Oversight of AI Use Cases & Solutions

• Support governance oversight for: 

  • Internal AI initiatives across SCOR
  • AI solutions developed by SCOR for its clients
• Ensure AI solutions are assessed for compliance with: 
  • Regulatory obligations
  • Internal policies and standards
  • Ethical, security, and risk management requirements
• Engage with solution owners, technology teams, and business stakeholders to embed governance and guardrails early in AI initiatives.

4. AI Risk, Ethics & Guardrails

• Contribute to identifying, assessing, and mitigating AI‑related risks, including: 

  • Bias, fairness, explainability, robustness, and security
  • Model limitations and misuse risks
  • Data quality and provenance concerns
• Support the design of practical AI guardrails adapted to different types of AI solutions, from traditional machine learning models to advanced generative and agentic AI systems.

5. Cross‑Functional Collaboration

• Work closely with internal SCOR stakeholders, including: 
  • Model Risk Management
  • Data teams
  • Compliance, Legal, and Risk Management
  • Technology and Security
  • SCOR Digital Solutions and business units
• Act as a governance partner, helping teams understand requirements and translating them into concrete implementation actions. 

6. Business Value & User Engagement

• Engage closely with business stakeholders, solution owners, and users to understand objectives, constraints, and value drivers of AI initiatives.
• Position AI governance as an enabler of safe and valuable AI adoption, supporting teams in making informed and pragmatic design and deployment choices.
• Help translate governance principles into actionable guidance that supports real‑world decision‑making, rather than purely theoretical or compliance‑only outcomes.

7. AI Community & Enablement

• Support and engage with AI communities within SCOR, contributing to: 
  • Awareness of responsible AI practices
  • Governance‑by‑design adoption
  • Continuous improvement through feedback from practitioners
• Contribute to internal communication, guidance materials, and governance enablement initiatives.

8. AI Ecosystem & Market Awareness

• Maintain continuous awareness of the evolving AI ecosystem, including emerging models, tools, platforms, and usage patterns, to inform governance standards and risk assessments.
• Assess the implications of new AI capabilities (e.g. generative and agentic AI) on SCOR’s governance framework, control expectations, and regulatory posture.
• Contribute informed perspectives to internal discussions by linking AI market developments to practical governance, risk, and compliance considerations.

Required experience & competencies :

Experience

• Experience in AI Governance, Data Governance, Model Risk, Technology Risk, or related domains
• Experience working in or with regulated environments (e.g. financial services, insurance, banking, or similar) is strongly preferred
• Exposure to regulatory or compliance‑driven frameworks is an advantage (e.g. EU AI Act, model risk management frameworks, data protection).

Technical & AI Knowledge

• Good understanding of different types of AI systems, including: 
  • Traditional machine learning models (supervised vs. unsupervised learning)
  • Classification, clustering, anomaly detection, forecasting, NLP
• Familiarity with modern AI approaches such as: 
  • Generative AI
  • Agents and agentic AI
  • Copilots and coding agents
• Solid understanding of: 
  • AI limitations and failure modes
  • Bias, explainability, robustness, security, and monitoring challenges
  • Principles of responsible and ethical AI.

Soft Skills

• Strong analytical and structured thinking
• Ability to translate complex technical and regulatory topics into clear, practical guidance
• Excellent collaboration skills across technical, business, and control functions

Clear written and verbal communication skills in English.

Required Education 

• Bachelor’s or Master’s degree in a relevant field (e.g. Data Science, Computer Science, Engineering, Applied Mathematics, Risk, Law with technology focus, or similar).

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