Turn complex structured credit into clear insights that shape investment decisions. Join a high-impact Credit Risk team where your analysis directly informs senior stakeholders across Treasury and Chief Investment Office. You will combine structured finance expertise with hands-on analytical execution, building scalable solutions that enhance risk and investment decision-making. This role offers the opportunity to bridge credit insight and technology to deliver real business impact.
As a Quantitative Credit Vice President – Structured Products in Credit Risk within Corporates, Treasury and Chief Investment Office, you deliver deep structured credit insights while building scalable analytical solutions. You will combine expertise in structured finance with hands-on technical execution, using modern tools such as Python and automation. We work together to translate complex credit risks into clear, actionable insights that support investment and risk decisions. You will partner with technology teams to scale solutions and influence strategic analytics development.
Job responsibilities
- Conduct in-depth portfolio and deal reviews, assessing collateral, structures, credit drivers, and loss scenarios
- Translate credit analysis into clear, actionable insights to inform investment and risk decisions
- Support senior management with asset-class-specific analyses and prepare materials for senior risk forums
- Prototype and build analytical solutions using Python and automation frameworks
- Manage the full analytics lifecycle, including problem definition, prototyping, validation, and scaling
- Leverage AI-assisted tools to accelerate delivery while maintaining quality and governance standards
- Develop and validate credit loss models including probability of default, loss given default, and exposure at default
- Design scenario analysis, stress testing, and sensitivity frameworks to assess tail risks
- Collaborate with cross-functional teams across investment, risk, and technology
- Drive initiatives end-to-end from problem framing to solution delivery
- Communicate insights clearly to ensure alignment across stakeholders
Required qualifications, capabilities, and skills
- Experience in credit risk, structured finance, or quantitative finance with expertise in securitized products such as CLO, RMBS, CMBS, or ABS
- Strong knowledge of deal documentation, deal structures, and credit underwriting
- Practical knowledge of credit loss modeling and portfolio risk frameworks
- Strong Python programming skills for modeling, data analysis, and automation
- Ability to develop analytical solutions to address business challenges
- Strong communication and collaboration skills to work with cross-functional teams
Preferred qualifications, capabilities, and skills
- Experience with solution architecture for analytical or risk platforms and familiarity with governance and control frameworks for model risk
- Hands-on experience applying AI or machine learning methods to credit analytics and decision support
- Experience working with technology teams to scale models and tools into production
- Knowledge of regulatory stress testing and reserve provisioning frameworks such as CCAR and CECL