Assistant Vice President, Quant, Structured Finance Analytics

Morningstar

. Execute proprietary research for credit rating models, including factor models and predictive models for ABS, CMBS, RMBS and Structured Credit .

Posted 9/23/2026full-timeFrankfurt • GermanyLead💰 €69,000 - €104,467 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in quantitative modeling and analytics, with a strong foundation in statistical methods and programming. Proficient in developing and enhancing credit rating models and frameworks using Python and C++ while collaborating across technical and non-technical teams.

Highest-signal resume keywords

Quantitative ModelingPython ProgrammingC++ ProgrammingStatistical AnalysisCredit Rating Methodology

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Statistical ModelingNumerical AnalysisStochastic CalculusMonte Carlo SimulationData AnalysisCloud Application DevelopmentResearch WritingTechnical DocumentationFactor ModelsPredictive Models

Soft Skills

CollaborationCommunicationProblem-Solving

Tools & Technologies

NumPyPandasScikit-LearnSciPyAWS

Certifications & Qualifications

CQF

Industry Keywords

RMBSABSCLOSecuritisation ProductsCredit Ratings

Tech Stack

Tools & technologies

AWSCloudNumpyPandasPythonScikit-LearnC++

About the role

Key responsibilities & impact

Execute proprietary research for credit rating models, including factor models and predictive models for ABS, CMBS, RMBS and Structured Credit
Support rating methodology development and implement quantitative models such as credit predictive models
Develop, maintain and enhance proprietary Python and C++ libraries for model building
Leverage structured and unstructured datasets to build quantitative frameworks supporting analyst decision-making
Develop analytics-based solutions for information ingestion, storage, computation, training/inference and validation
Participate in analyst conversations to understand ongoing issues and market trends
Contribute to quantitative research papers supporting model development, methodology enhancements and analytical innovation
Collaborate with Credit Ratings, Credit Practices, Methodology Review Function, Data Engineering and Technology teams

Requirements

What you’ll need

Bachelor’s degree in Mathematics, Engineering, Physics, Economics, Finance, Statistics, or a related quantitative discipline
Master’s degree or PhD preferred in a related quantitative discipline
Minimum 5 years of experience within a rating agency
Minimum 5 years of hands-on experience in RMBS/ABS/CLO defaults and losses modelling
Coding skills in Python or C++
Experience writing research articles and/or technical documentation using LaTeX
Strong knowledge of statistical modelling, probability theory, numerical analysis and stochastic calculus
Strong knowledge of numerical methods, including numerical integration, Monte Carlo simulation, root-finding and optimisation techniques
Excellent understanding of securitisation products
Ability to understand business and technical requirements and serve as a conduit between technical and non-technical departments
CQF or postgraduate degree in quantitative finance, economics, or STEM fields highly desired
Exposure to NumPy, Pandas, Scikit-Learn and SciPy
Ability to perform rigorous data analysis on large datasets
Experience developing cloud applications, preferably AWS

Benefits

Comp & perks

20% annual bonus target
Hybrid work environment with regular in-person collaboration
Four days in-office each week in most locations
Tools and resources to engage meaningfully with global colleagues
Other benefits available to enhance flexibility as needs change