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Assistant Vice President, Quantitative Analyst, Structured Finance
- Pay
EUR 63,400–92,133/year · BaseAnnual period assumed — pay source
Base Salary Compensation Range EUR 63,400.00-92,133.00 Bonus Target:
Read the full posting- Work setting
- Not stated
- Employment
Full-time — employment source
Employment type in the employer’s posting: Full time
From the employer’s posting
What you’ll work on
Full postingSupport rating methodology development and implement credit predictive models
Build quantitative frameworks from structured and unstructured datasets
Design and develop solutions for data ingestion, storage, computation and validation
Write quantitative research papers supporting model and methodology work
From the employer’s posting
Support rating methodology development and participate in the implementation of quantitative models such as credit predictive models.
Leverage structured and unstructured datasets to build new quantitative frameworks to assist analysts in informed decision making.
taking ownership of the design and development of solutions to scale out information ingestion, storage, computation (training/inference), validation.
Contribute to the development and writing of quantitative research papers supporting model development, methodology enhancements, and analytical innovation.
What you’ll bring
All qualificationsCore experience
- Bachelor’s degree; Master’s degree or PhD preferred in Mathematics, Engineering, Physics, Economics, Finance, Statistics, or a related quantitative discipline.
- Ability to perform rigorous data analysis on large datasets.
- Strong knowledge of statistical modelling, probability theory, numerical analysis and stochastic calculus.
- Experience developing cloud applications (AWS preferably).
- Strong knowledge of numerical methods (numerical integration, Monte Carlo simulation, root-finding and general optimisation techniques).
- Excellent understanding of securitisation products.
Qualification wording
Bachelor’s degree; Master’s degree or PhD preferred in Mathematics, Engineering, Physics, Economics, Finance, Statistics, or a related quantitative discipline.
Ability to perform rigorous data analysis on large datasets.
Strong knowledge of statistical modelling, probability theory, numerical analysis and stochastic calculus.
Experience developing cloud applications (AWS preferably).
Strong knowledge of numerical methods (numerical integration, Monte Carlo simulation, root-finding and general optimisation techniques).
Excellent understanding of securitisation products.
Education & alternatives
Requirements - Bachelor’s degree; Master’s degree or PhD preferred in Mathematics, Engineering, Physics, Economics, Finance, Statistics, or a related quantitative discipline. - Minimum 5 years of experience within a rating agency (preferred) or financial institution.
Posting record
Report an error- Status in our records
- Live
- First seen by us
- Oct 2, 202633 days ago
- Recorded sightings
- 30
- Last seen by us
- Nov 4, 2026
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
How this job compares
Morningstar is hiring
6 open jobs
Open jobs by the week we first saw them, last 12 weeks.
- Hiring at a steady pace
- Takes jobs down at a usual pace
See how this role fits your experience
Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.
- Python
- AWS
- NumPy
- pandas
- scikit-learn
- SciPy
- C++
Where the posting names them
- Support rating methodology development and participate in the implementation of quantitative models such as credit predictive models. - Develop, maintain and enhance proprietary Python and C++ libraries related to model building. - Leverage structured and unstructured datasets to build new quantitative frameworks to assist analysts in informed decision making.
- Minimum 5 years of hands-on experience in RMBS/ABS/CLO defaults and losses modelling. - Coding skills in a major programming language Python or C++ and experience writing research articles and/or technical documentation using LaTeX. - Strong knowledge of statistical modelling, probability theory, numerical analysis and stochastic calculus.
- CQF or postgraduate degree in quantitative finance, economics, or STEM fields is highly desired. - Exposure to main Python packages for numerical computing and Machine Learning / Data Science (NumPy, Pandas, Scikit-Learn and SciPy). - Ability to perform rigorous data analysis on large datasets.
- Ability to perform rigorous data analysis on large datasets. - Experience developing cloud applications (AWS preferably). If you receive and accept an offer from us, we require that personal and any related investments be disclosed confidentially to our Compliance team. These investments will be reviewed to ensure they meet Code of Ethics requirements. If any conflicts of interest are identified, then you will be required to liquidate those holdings immediately. In addition, dependent on your department and location of work certain employee accounts must be held with an approved broker (for example all, U.S. employee accounts). If this applies and your account(s) are not with an approved broker, you will be required to move your holdings to an approved broker.
Your next step
Complete your application on morningstar.wd5.myworkdayjobs.com. The employer’s form will show what is required.
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Already applied? Track this application
Has Morningstar posted this job before?
Yes. We’ve followed one other Assistant Vice President, Quantitative Analyst, Structured Finance job there since September 2026. It is still up.
About the role
We file this job under Data Scientist, by the work the posting describes.
Data scientists use statistics and models to answer harder questions, such as whether a change worked, what demand will look like next quarter, or which customers are likely to leave.
Postings usually ask for Python or R, SQL, statistics, experiment design and common machine learning methods.
Unlike an ML engineer, a data scientist's main output is often an analysis or a first model, not software running inside a product.
US government figures for data scientists
- Median yearly pay, May 2025
- $120,230
- Expected change, 2025 to 2035
- 34.6% more jobsagainst 3.5% for all jobs
Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-2051.
Job description
About the Team
The Structured Finance Analytics Team is composed of a Quant team, a Data Analytics team, a Solutions team, and a Cashflow Modelling team. The Quant team has been growing over the last few years, comprising a global team of a dozen people today, located in the US and in Europe. The Quant team builds models and analytical tools to help rating analysts assess the credit risk of a transaction.
The Role
As a Quant Analyst you will execute proprietary research for building various types of credit rating models, such as factor models and predictive models covering asset classes of ABS, CMBS, RMBS and Structured Credit. The Quant team will collaborate with members from the Credit Ratings, Credit Practices, Methodology Review Function, Data Engendering and Technology teams to create class leading models that are as innovative as understandable in the marketplace.
Responsibilities
- Support rating methodology development and participate in the implementation of quantitative models such as credit predictive models.
- Develop, maintain and enhance proprietary Python and C++ libraries related to model building.
- Leverage structured and unstructured datasets to build new quantitative frameworks to assist analysts in informed decision making.
- Assisting development of analytics-based solutions, taking ownership of the design and development of solutions to scale out information ingestion, storage, computation (training/inference), validation.
- Participate in analyst conversations to understand ongoing analyst issues and merging market trend.
- Contribute to the development and writing of quantitative research papers supporting model development, methodology enhancements, and analytical innovation.
Requirements
- Bachelor’s degree; Master’s degree or PhD preferred in Mathematics, Engineering, Physics, Economics, Finance, Statistics, or a related quantitative discipline.
- Minimum 5 years of experience within a rating agency (preferred) or financial institution.
- Minimum 5 years of hands-on experience in RMBS/ABS/CLO defaults and losses modelling.
- Coding skills in a major programming language Python or C++ and 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 (numerical integration, Monte Carlo simulation, root-finding and general optimisation techniques).
- Excellent understanding of securitisation products.
- Understanding both business and technical requirements, and the ability to serve as a conduit between technical and non-technical departments.
Nice to have
- CQF or postgraduate degree in quantitative finance, economics, or STEM fields is highly desired.
- Exposure to main Python packages for numerical computing and Machine Learning / Data Science (NumPy, Pandas, Scikit-Learn and SciPy).
- Ability to perform rigorous data analysis on large datasets.
- Experience developing cloud applications (AWS preferably).
If you receive and accept an offer from us, we require that personal and any related investments be disclosed confidentially to our Compliance team. These investments will be reviewed to ensure they meet Code of Ethics requirements. If any conflicts of interest are identified, then you will be required to liquidate those holdings immediately. In addition, dependent on your department and location of work certain employee accounts must be held with an approved broker (for example all, U.S. employee accounts). If this applies and your account(s) are not with an approved broker, you will be required to move your holdings to an approved broker.
Base Salary Compensation Range
EUR 63,400.00-92,133.00
Bonus Target:
20% Annual
Morningstar's hybrid work environment gives you the opportunity to collaborate in-person each week as we've found that we're at our best when we're purposely together on a regular basis. In most of our locations, our hybrid work model is four days in-office each week. A range of other benefits are also available to enhance flexibility as needs change. No matter where you are, you'll have tools and resources to engage meaningfully with your global colleagues.
Source details
Source notes
Source excerptsSelected passages from the saved posting. Check the full description for conditions and exceptions.
- Pay
Base Salary Compensation Range EUR 63,400.00-92,133.00 Bonus Target:
- Location & working pattern
Madrid
20% Annual Morningstar's hybrid work environment gives you the opportunity to collaborate in-person each week as we've found that we're at our best when we're purposely together on a regular basis. In most of our locations, our hybrid work model is four days in-office each week. A range of other benefits are also available to enhance flexibility as needs change. No matter where you are, you'll have tools and resources to engage meaningfully with your global colleagues.
- Work authorization
No clear work-authorization passage found. Eligibility is unconfirmed.