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Global Non-Financial Risk Assessments & Control Program Lead
Company | Morgan Stanley |
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Location | New York, NY, USA |
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Salary | $165000 – $275000 |
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Type | Full-Time |
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Degrees | Bachelor’s |
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Experience Level | Senior, Expert or higher |
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Requirements
- An undergraduate degree (B.A., B.S., or equivalent) required
- 10-15 years of experience in Financial Services
- Strong technical understanding of the financial services regulatory environment, with a focus on Operational, Compliance or Financial Crimes Risk
- Excellent communication and influencing skills, both verbal and written, and an ability to present ideas concisely and visually
- Proven track record of designing or leading strategic enhancements to risk or control frameworks
- Adept at influencing senior stakeholders and aligning cross-functional teams in a matrixed environment
- Excellent analytical skills and a strong ability to work with large data files and spreadsheets
Responsibilities
- Lead the strategic enhancement and modernization of the Non-Financial Risk (NFR) Framework
- Design innovative and forward-thinking risk framework components to drive real risk management value
- Challenge conventional thinking and bring creative, outside-the-box solutions to strengthen risk identification, mitigation, and reporting practices
- Translate complex risk concepts into clear, practical methodologies and tools used across the First and Second Lines of Defense
- Collaborate with cross-functional teams (Risk, Compliance, Technology, Legal, Business Lines) to co-create fit-for-purpose frameworks and controls
- Own program delivery, including project planning, execution oversight, and reporting for enterprise-wide risk transformation initiatives
- Build strong, trust-based relationships with senior leaders to align on strategic priorities and drive adoption of framework enhancements
- Establish and run governance structures, steering committees, and working groups to ensure timely decision-making and accountability
- Collaborate with Data and Analytics on unified categorization model, data visualization, data objects
Preferred Qualifications
No preferred qualifications provided.