Hybrid SVP, Structured Finance Quant Modeling & Leadership

Morningstar; Greater London; Hybrid; GBP 135,000 - 196,000; Full time

Job summary

Morningstar is seeking a Senior Vice President in the Quant team to provide hands-on technical leadership in structured finance credit rating modelling across RMBS, CMBS, ABS and Structured Credit. You will collaborate with Credit Ratings, Credit Practices, and Data Engineering to deliver rigorous models.

You will mentor analysts, drive model development and ensure robustness, while leveraging Python and C++ to build transparent, well-justified solutions. Hybrid work setup offered.

Qualifications

• Master's degree in Mathematics, Engineering, Physics, Economics, Finance, Statistics, or related quantitative field; PhD preferred.
• 10+ years of relevant professional experience in quantitative credit risk, including structured finance default and loss models for RMBS/CMBS/ABS/CLOs.
• Strong programming skills in Python or C++ and ability to write clear research articles or technical documentation.
• Rigorous data analysis on large datasets.
• Strong mathematical judgement and knowledge of statistical modelling, stochastic calculus and numerical methods.

Responsibilities

• Take hands-on ownership of design, implementation and enhancement of structured finance credit models.
• Lead complex model and methodology development projects across multiple teams.
• Develop and maintain proprietary Python and C++ modelling libraries.
• Engage with rating analysts to translate business needs into modelling approaches.
• Mentor quantitative analysts and review models, derivations and code.
• Explain complex quantitative concepts to non-technical colleagues clearly.

Skills

Python

C++

Quantitative analysis

Data analysis

Stochastic calculus

Education

Master's degree

PhD preferred

Tools

NumPy

Pandas

Scikit-Learn

SciPy

AWS

LaTeX

Job description

Morningstar is seeking a Senior Vice President in the Quant team to provide hands-on technical leadership in structured finance credit rating modelling across RMBS, CMBS, ABS and Structured Credit. You will collaborate with Credit Ratings, Credit Practices, and Data Engineering to deliver rigorous models.

You will mentor analysts, drive model development and ensure robustness, while leveraging Python and C++ to build transparent, well-justified solutions. Hybrid work setup offered.