Quantitative Analyst

The Team:

DBRS Morningstar is a global credit ratings business, currently with 700 employees in eight offices globally. 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. DBRS Morningstar is committed to empowering investor success, serving the market through leading-edge technology and raising the bar for the industry. DBRS Morningstar is a market leader in Canada, the U.S. and Europe in multiple asset classes. DBRS Morningstar is driven to bringing more clarity, diversity of opinion, and responsiveness to the ratings process. DBRS Morningstar’s approach and size provide the agility to respond to customers’ needs, while being large enough to provide the necessary expertise and resources.

The Role:
• Building, validating, testing and reviewing of quantitative models (default models, cashflow models, capital models, regression models, time series models) that support our ratings across asset classes of ABS, CMBS, Covered Bond, RMBS, Structured Credit, Corporates.
• Evaluating and enhancing stability, conceptual soundness, assumptions, and mathematical logic of existing models
• Implementing models in an industrial strength language (Python, Spark, DASK etc.) as needed.
• Developing insights on large scale data, performing ad-hoc data cleaning and statistical analysis as needed
• Communicating results to rating analysts, senior management and other key stakeholders
• Developing reports for regulators and other external parties
• Managing, mentoring a team of junior quantitative modelers

Minimum Requirements:
• MS/PhD in a quantitative discipline (econometrics, statistics, mathematics, physics, etc.) with strong project portfolio
• Minimum 1 year of industry experience in quantitative modeling of credit risk
• Strong quantitative/statistical skills in the field of predictive analytics with broad knowledge of regression analysis, time series analysis, Monte Carlo simulations, artificial intelligence and data mining algorithms
• Strong coding skills, with preference for Python
• Excellent aptitude for application of mathematical and quantitative methods to business problems
• Ability to explain, defend, garner support for and communicate technical and statistical components of models to both internal and external business stakeholders
• Familiarity with Agile software engineering practices
• Intellectual curiosity for the world of quantitative research

Nice to have:

• Experience with modeling financial products and/or securitization
• Experience with SAS/R, SQL, C#, Python, C++
• Experience with distributed data processing ecosystems (Spark, DASK etc.)
• Experience developing using Git or other collaborate workflow systems
• Experience with AWS
• CFA Qualification