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Morningstar DBRS is a global credit ratings business, formed through the July 2019 acquisition of DBRS by Morningstar, Inc., the ratings business is the fourth-largest provider of credit ratings in the world. Morningstar DBRS is committed to empowering investor success, serving the market through leading-edge technology and raising the bar for the industry. Morningstar DBRS is a market leader in Canada, the U.S. and Europe in multiple asset classes. 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 from two to eight people today. The Quant team builds models and analytical tools to help rating analysts assess the credit risk of a transaction. Although some projects are global, this team mostly covers US needs. 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, 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 and demonstrating the ability to collaborate with rating analyst, credit practices and tech teams. The ideal candidate will demonstrate quantitative skills in statistics, machine learning, numerical methods and software engineering. This position reports to the Associate Managing Director who leads the team. Responsibilities: * Support rating methodology development and participate in the implementation of quantitative models such as credit predictive models. * 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: * Postgraduate degree in mathematics, quantitative finance, financial engineering, statistics or physics is highly desired. * 4 - 7 years of investment research , structured products, asset backed finance, credit modelling or rating agencies experience with emphasis on fixed income research / analysis * Coding skills in a major programming language (Python, C/C++ or C#) or SAS / R / MATLAB. * Strong Knowledge of probability theory, numerical analysis and stochastic calculus. * Strong Knowledge of numerical methods (numerical integration, Monte Carlo simulation, root-finding and general optimisation techniques). * At least 2 years of experience in US RMBS defaults and losses modelling. Other asset classes within Structured Finance (ABS, CLOs) are also acceptable. Nice to have: * Ability to perform rigorous data analysis on large datasets. * Exposure to main Python packages for numerical computing and Machine Learning / Data Science (NumPy, Pandas, Scikit-Learn and SciPy). * 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. About UsMorningstar DBRS is a leading provider of independent rating services and opinions for corporate and sovereign entities, financial institutions, and project and structured finance instruments glo