About the Role:

Primary role of the Quantitative Analytics Manager in the Retail Modelling, is to manage and lead multiple teams of Quantitative Analytics specialists. This team is responsible for the development and maintenance of regulatory models (CCAR, CECL, Basel) for the retail portfolio. This team leverages extensive business knowledge, advanced programming skills, modeling techniques and analytics to serve as a subject matter experts, analysts, advisors and consultants to deliver best in class models used for regulatory requirements of the bank.

Responsibilities:

• Lead multiple teams to perform various complex activities related to predictive modeling. Provide guidance and analytical support for the development, enhancement and maintenance of Credit ACL, CECL, Basel and CCAR models for Home Lending, Auto and Unsecured (Cards, Loans, Small Business Loans, Other) portfolios.

• This position will be responsible for overseeing design, development, documentation and implementation of various forecasting and capital models such as, but not limited to, PD, LGD, EAD, Business Loss Forecasting, Fee Income & Expense and Balance Projection models

• Work closely with the implementation and monitoring team for flawless execution and regular monitoring of these models.

• Partner with various stakeholders in line of business, model implementation and production team, Model Risk Management, Model Governance to ensure flawless and timely delivery of models in compliance with Model Risk Policies and Regulatory Frameworks.

• Identify opportunities and deliver process improvements, standardization, rationalization and automations. Enhance and standardize performance analysis, reporting packages and business loss forecast processes

• Lead and support strategic direction for the Retail modeling group

Essential Qualifications:  

• Overall experience around 12+ years in similar role 

• Master’s degree or PhD in a quantitative fields such as applied mathematics, statistics, engineering, management, finance, economics, econometrics or computer sciences

• Experience in credit risk analytics including understanding of end-to-end model lifecycle activities such model development, documentation, monitoring and validation.

• Hands-on experience in statistical modeling techniques such as regression, time-series, survival modeling and machine learning

• 12+ years of advanced programming expertise in SAS/Python

• Strong technical skills and problem-solving skills

• Strong project management skills with ability to prioritize work, meet deadlines, achieve goals, and work under pressure in a dynamic and complex environment

• Excellent verbal, written, and interpersonal communication skills

• Strong ability to develop partnerships and collaborate with other business and functional areas

• Knowledge and understanding of issues or change management processes

• Flexibility with changing priorities

Desired Qualifications:  

• Ability to partner and influence senior management teams on critical projects.

• Ability to prioritize work, meet deadlines, achieve goals and work under pressure in a dynamic and complex environment

• Detail oriented, results driven, and has the ability to navigate in a quickly changing and high demand environment while balancing multiple priorities

• Understanding of bank regulatory data sets and other industry data sources

• Ability to research and report on a variety of issues using problem solving skills

• Ability to interact with a high level of professionalism with all levels of team members and management

• Ability to make timely and independent judgment decisions while working in a fast-paced and results-driven environment