Sr Manager / Manager, Risk Analytics-ALLL Modeling

Job Description

Your Opportunity

Our Opportunity:

The Risk Analytics team is situated within Financial Risk Management under the Corporate Risk Management organization. The team’s primary functions are to provide quantitative research and modeling of market and credit risks, covering a wide range of products including: mortgage loans, home equity lines of credit, margin, deposit and fixed income businesses.

What you’re good at

What you’ll do:

We are looking for a Senior Analyst of Risk Analytics to help the model execution and development efforts relating to retail credit loss forecasting.

The incumbent will play a crucial role in executing and refining the current loss forecasting process for HELOC, including developing quantitative analysis to support the ongoing credit risk model development efforts. You will have knowledge of lending products and provide enhancements and support to existing models as well as developing new model initiatives. This will be an individual contributor role reporting to the Director of Risk Analytics.

Key responsibilities will include, but are not limited to:

• Execute the process for loss forecasting on HELOC portfolio (including for Capital Stress Testing)
• Perform statistical and econometric analyses of the portfolio
• Implement process improvements using technology
• Assist in the development of additional credit loss forecasting models
• Enhance model documentation, including additional backtesting, developmental evidence, and model limitations
• Utilize project management and communication skills to ensure project deliverables are understood and achievable.

What you have

What you have:

The Sr. Analyst, Risk Analytics must be proficient with quantitative and analytical methods and techniques, and use technology to query databases and prepare documentation for senior management. You should be familiar with best practices as they relate to the development of advanced quantitative models, including source code management, input variable stress analysis and overall model validation techniques.

• A degree in one of the following fields is required: finance, economics, financial engineering, applied and computational mathematics, and other disciplines in physical sciences or engineering
• Proficiency in use of computational mathematics and/or statistical techniques
• 2-5 years of experience in credit risk and exposure to lending products
• Strong quantitative and appropriate coding skills necessary to develop and refine
• Proficiency in statistical packages such as SAS, R, Matlab or Stata is desirable (R is preferred)
• Strong technical skills with experience using relational databases
• Strong communication skills with ability to translate mathematical and statistical concepts for non-technical audiences, including senior management and auditors.
• Knowledge of lending products (particularly first mortgage and HELOCs) and their performance drivers preferred