Outsourcing Operational Risk Management Lead - Vice President

JPMorgan Chase JPMorgan Chase · Banking · Singapore · Corporate Sector

This role is responsible for overseeing operational risks related to third-party/outsourcing within a financial institution. A key aspect involves contributing to the development and implementation of AI-enhanced risk monitoring capabilities, specifically leveraging LLM-based functionalities to improve risk assessment and oversight. The role requires experience in financial services risk management, control assessments, and stakeholder influence, with a specific requirement for experience using AI models to drive value in risk management.

What you'd actually do

  1. Own regional 2LOD oversight for Third Party / Outsourcing Risk: Set the regional agenda and provide credible challenge to LOB/CF and Location leads to ensure complete coverage, consistent execution, and timely escalation of material third party risks.
  2. Lead independent control assessments and risk opinions: Drive objective evaluations of third party control environments and mitigation plans (design/operating effectiveness where applicable), synthesize conclusions, and deliver clear risk positions and recommended actions.
  3. Coordinate jurisdictional regulatory alignment with Compliance: Translate evolving regional regulatory expectations into practical oversight requirements; partner with Compliance to ensure adherence across CTPO/Global Security and LOB/CF teams and to support regulatory/audit readiness.
  4. Deliver thematic risk insights and executive reporting: Run thematic analyses using KRIs/KPIs, control performance data, and issues/incidents to identify trends and emerging risks; communicate regional risk posture, hotspots, and decisions required to senior stakeholders.
  5. Contribute to the development of AI-enhanced risk monitoring capabilities, partnering with technology teams to drive LLM-based capabilities

Skills

Required

  • Minimum 8 years in financial services or multinational corporations (MNCs) in roles related to risk management, resiliency, outsourcing program management, or controls-focused areas.
  • AI/ML enablement for risk: Experience using AI models and driving value from them required
  • Demonstrated experience assessing third party risk and controls, performing due diligence/control reviews, and providing effective challenge and risk recommendations.
  • Proven 2LOD third party / outsourcing risk leadership: Experience forming risk views, challenging 1LOD, and driving closure on control gaps and material risk issues across multiple stakeholders.
  • Strong governance execution: Ability to establish decision forums, drive alignment, document outcomes, and ensure follow through across lines of defense and regions.
  • Regulatory and audit-ready mindset: Demonstrated partnership with Compliance and capability to operationalize jurisdictional requirements into sustainable oversight practices and evidence.
  • Thematic analytics & risk storytelling: Ability to turn metrics and control/issue data into prioritized insights and crisp executive narratives (what changed, why, so what, now what).
  • Technology risk depth for third party oversight: Strong command of cyber, data protection, and resiliency/BCP, with practical ability to assess third party architecture resilience (cloud shared responsibility; HA/DR patterns).
  • Executive-level communication and stakeholder influence: Confident, concise communicator with the ability to negotiate and drive decisions with senior stakeholders.
  • Demonstrated ability to work effectively in cross-functional teams and drive initiatives to completion in a complex, matrixed organization.

Nice to have

  • Domain Expertise: Specific expertise in third party risk management, sourcing & procurement, operational risk, and control management is highly desirable.
  • Hands-on dashboards / automation: Building automated reporting and monitoring solutions (vs. only consuming analytics).
  • Deep cloud engineering expertise: Advanced architecture specialization beyond assessment needs.
  • Day-one familiarity with specific regional regulators/regulatory guidelines (e.g., MAS/HKMA/OJK/BNM)
  • Data-Driven Risk Analysis: Ability to analyze risk concentration areas and risk profiles by integrating and interpreting data from both internal and external sources, enabling comprehensive assessment of residual risk posture.
  • Complex Data Management: Experience working with large, complex da

What the JD emphasized

  • AI/ML enablement for risk: Experience using AI models and driving value from them required

Other signals

  • AI/ML enablement for risk
  • Experience using AI models and driving value from them required
  • Contribute to the development of AI-enhanced risk monitoring capabilities
  • partnering with technology teams to drive LLM-based capabilities