Camellia Carbonaro
Model Risk Associate @ Morgan Stanley | Quantitative Risk | CCAR & Stress Testing | Regulatory Compliance | Applied Mathematics
- Role
- Model Risk Associate at Morgan Stanley
- Location
- New York, NY, US
- LinkedIn followers
- 500 followers
About Camellia Carbonaro
Model Risk Associate at Morgan Stanley with a background in Applied Mathematics and a growing track record in model risk, regulatory compliance, and operational risk at leading financial institutions.Currently leading CCAR, annual capital planning, and quarterly stress testing initiatives at Morgan Stanley, coordinating across Model Risk Management, validation teams, and business units to ensure timely regulatory delivery.My path into model risk came through regulatory and operational risk roles at MUFG, where I developed hands-on experience in RCSA execution, issue management, control testing, and ORM reporting — giving me a broader risk perspective that I bring into model risk work.My quant background in Applied Mathematics complements the technical demands of model risk, and I\'m focused on deepening my expertise in this space at the senior level.
Experience
Model Risk Associate
Mar 2026 — Present · New York, NY, US
Led end-to-end execution of CCAR, annual capital planning, and quarterly stress testing initiatives, coordinating across Model Risk Management (MRM), validation teams, and business units to ensure timely regulatory delivery.* Drove regulatory issue remediation efforts, managing cross-functional stakeholders, deliverable timelines, and escalation of critical risks to support supervisory expectations.* Partnered with model validation and governance teams to establish execution frameworks, enforce deliverable schedules, and maintain momentum across high-impact regulatory programs.
Education
Bergen County Academies
High School Diploma, Academy of Medical Science Technology
2010 — 2014
The College of New Jersey
Bachelor of Science - BS, Applied Mathematics
2014 — 2019
Harvard Extension School
Master's degree, Data Science
2030
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