Analyst, Quant, Structured Finance Analytics (Mathematical Modelling)

bout the role:

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 and is now composed by 13 analysts. As part of the Quant team, you will build models models and analytical tools to help rating analysts to assess the credit risk of a transaction. Although some projects are global, this team mostly covers European needs.  

As a Quant Analyst, you will execute proprietary research for building various types of statistical credit rating models, such as factor models and predictive models covering asset classes of ABS, CMBS, Covered Bond, RMBS and Structured Credit.  

The Structured Finance Ratings Modeling team will collaborate with members from the Credit Ratings, Credit Practices, Independent Review, Data and Technology teams to create class leading models that are as innovative as they are easy to understand in the marketplace.  

You will be expected to adopt an "iron sharpens iron" attitude where the focus is on making everyone better. The ideal candidate will demonstrate solid quantitative skills in statistics and mathematics, machine learning, numerical methods, and software engineering. This position reports to the Associate Managing Director who leads the team. 

Responsibilities: 

• Apply statistical and mathematical modelling to the development and implementation of credit rating methodologies into quantitative models and tools. 

• Maintain and enhance proprietary Python and R libraries related to model building.  

• Leverage structured and unstructured datasets to build new Quant 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 information ingestion, storage, computation (training/inference), validation.  

• Participate in analyst conversations for understanding ongoing analyst issues.  

Requirements: 

• Master’s degree in mathematics, engineering or physics.  

• Up to 2 years of investment research / rating agencies experience with emphasis on fixed income research / analysis, credit modelling.  

• Knowledge of probability theory, numerical analysis and stochastic calculus.  

• Knowledge of numerical methods (numerical integration, Monte Carlo simulation, root-finding and general optimisation techniques).  

• Coding skills in a major programming language such as Python, C/C++ or R / MATLAB. 

Nice to have:  

• CQF certification.  

• 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 applications on cloud (AWS preferably).  

• Understanding of both business and technical requirements, and the ability to serve as a conduit between technical and non-technical departments.  

• Familiarity fixed income and structured finance. 

Base Salary Compensation Range

EUR 42,000.00-57,800.00

Bonus Target:

10% Annual

Base Salary Compensation Range

Bonus Target:

We expect the compensation and target bonus for this role to fall within the stated range. The specific compensation offered will depend on the candidate’s qualifications, experience, and other job-related factors.

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.