VP-Analytics & Modeling
About the role
At Moody's, we unite the brightest minds to turn today’s risks into tomorrow’s opportunities. We do this by striving to create an inclusive environment where everyone feels welcome to be who they are—with the freedom to exchange ideas, think innovatively, and listen to each other and customers in meaningful ways. Moody’s is transforming how the world sees risk. As a global leader in ratings and integrated risk assessment, we’re advancing AI to move from insight to action—enabling intelligence that not only understands complexity but responds to it. We decode risk to unlock opportunity, helping our clients navigate uncertainty with clarity, speed, and confidence. If you are excited about this opportunity but do not meet every single requirement, please apply! You still may be a great fit for this role or other open roles. We are seeking candidates who model our values: invest in every relationship, lead with curiosity, champion diverse perspectives, turn inputs into actions, and uphold trust through integrity. Skills and Competencies Outstanding management skills and proved ability to operate with a high degree of autonomy and own initiative while ensuring quality and consistency. Deep quantitative expertise with ownership of business logic design for credit rating models across the model suite. Very strong understanding of fixed income and financial mathematics, including understanding of structured finance; ability to apply this to cross-sector model consistency and suite-level analytical decisions. Ability to oversee and challenge implementation of complex quantitative logic while ensuring analytical consistency, especially for novel analytical questions. Strong judgment, leadership, and stakeholder management skills in complex analytical environments. Good development skills in C#. Experience using C++, VBA or Matlab is a plus. Experience in guiding and challenging technical choices, not only implementing them. 10+ years of relevant professional experience in a quantitative role (e.g., credit risk, rating models, structured finance). Experience or interest in using AI tools to improve efficiency and effectiveness of analytical and development workflows Education PhD or MSc in Mathematics, Physics, or Statistics or a closely related quantitative discipline.