Lead Quantitative Analyst

Lead Quantitative Analyst
About the Team: Morningstar DBRS Credit Ratings, LLC is registered with the U.S. Securities and Exchange Commission as a nationally recognized statistical rating organization (NRSRO). Morningstar DBRS Credit Ratings issues credit ratings on a variety of security types including corporate and structured finance securities. This Morningstar subsidiary aims to increase market transparency by providing the highest-quality ratings, securities research, monitoring services, operational risk assessments, data, and tools.
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. Morningstar DBRS is driven to bringing more clarity, diversity of opinion, and responsiveness to the ratings process. Morningstar DBRS'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: As a Lead Quantitative Analyst you will execute proprietary research pertaining to various types of credit rating models, such as default models, cashflow models, capital models, regression models covering asset classes of RMBS, ABS, CMBS, Covered Bond, Structured Credit, Corporates, Financial Institutions and Sovereigns. The Credit Quant 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 involved in development of model frameworks from prototype phase to a fully-fledged, scalable, and client-facing service. Leveraging deep principles of Statistical, Machine Learning, AI principles and built on massive amounts of Financial datasets. Often, these services must be integrated into organization's platform of financial products, so that our clients can use these software tools in the investment decision-making process. We are looking for an individual who possesses strong Econometric knowledge coupled with technical skills and leverage them to build efficient model verification frameworks for evolving FinTech solutions. Alongside the person should have a passion for investment research.
Responsibilities:

• Team Leadership: Manage and mentor a small team of 2-4 quant analysts, providing guidance on modeling techniques and fostering a collaborative work environment.
• Strategic Decision-Making: Take responsibility for assessing the statistical significance of variables and determining their inclusion in models, ensuring robust and expected model performance.
• Model Oversight: Oversee the entire modeling process, from initial development through validation, and UAT ensuring that all models meet regulatory and internal standards.
• Stakeholder Engagement: Engage with senior management and other internal stakeholders to present modeling results and insights, influencing strategic decisions based on quantitative analysis.
• Innovative Review Methodologies: Develop and implement innovative model review methodologies to execute regulatory reviews and enhance the accuracy of statistical models.
• Model Building Blocks: Lead initiatives to develop reusable model building blocks to enhance accuracy and efficiency. Leverage advanced Python coding techniques to streamline workflows. Ensure that the models are aligned with latest Morningstar DBRS technology infrastructure.

Requirements:

• Minimum of 7-11 years of relevant experience working in Credit Modeling / Model Validation roles.
• Qualifications: MBA (Finance)/BTech/PHD (Math) from a Tier I college.
• Knowledge of finance, statistics, behavioral sciences.
• Familiarity fixed income products.
• Strong Analytical skills. Experience with large databases / datasets preferred.
• Knowledge and proficiency in a programming language (Python and packages as NumPy, Pandas, SciPy).
• Familiarity with AWS infrastructure is considered an added advantage.
• Experience working with large data/Data Warehouses.

Morningstar DBRS is an equal opportunity employer.
About Us
Morningstar DBRS is a leading provider of independent rating services and opinions for corporate and sovereign entities, financial institutions, and project and structured finance instruments globally. Rating more than 4,000 issuers and 60,000 securities, it is one of the top four credit rating agencies in the world.
Morningstar DBRS empowers investor success by bringing more transparency and a much-needed diversity of opinion in the credit rating industry. Our approach and size allow us to be nimble enough to respond to customers' needs in their local markets, but large enough to provide the necessary expertise and resources they require. Market innovators choose to work with us because of our agility, tech-forward approach, and exceptional customer service.
Morningstar DBRS is the next generation of credit ratings.
If you receive and accept an offer from us, we require that personal and any related investments be disclosed confidentiality to our Compliance team (days vary by region). 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.
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.
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