The Head of Unsecured, DDA/ODLOC Credit Risk will be responsible for Credit Risk Management of Citizens Unsecured Lending (Cards and Citizens Pays Pay), DDA and Overdraft Lines. The role reports to the Head of Consumer Credit Risk Management and Pricing. Will manage a team of credit and analytical colleagues that are responsible for all aspects of credit risk of Citizens BankCard and Citizens Pay (“Cpay”) portfolios including acquisitions, account management and collections oversight. The successful candidate will have deep subject matter experience in designing credit acquisition and account management strategies for Citizens Unsecured portfolios.

Primary responsibilities include:

• Retail Bank Card and Cpay credit cycle management
• DDA and ODLOC credit risk management
• Credit processing Transformation
• Develops procedures for performance of a variety of duties or performs complex duties within established policy guidelines.
• Responsible for a defined set of assignments, e.g., all financial activities for the department; is expected to determine and create necessary procedures to set priorities and meet specific goals and objectives of the function.

Qualifications:

• 10 + years of consumer credit risk management for Unsecured Products with extensive experience in the Credit Cards and BNPL product set
• Prior experience working with regulators (OCC) with examination preparation, support and findings remediation is critical.
• Experience with all three US credit bureau providers is a must.
• Use of credit scoring models for acquisition, account management and collections are required.
• Understanding of direct mail strategies related to customer acquisition is required.

Preferred Qualifications:

• Knowledge of Money In (DDA) is strongly.
• FinTech experience
• Understanding of Risk Base Pricing is
• Understanding of market leading credit tools such as those offered by FICO (Triad), Equifax (Ignite) and Experian (PowerCurve and Ascend) is strongly.

Education:

• Bachelor’s or Master’s degree in Statistics or Data Science required.
• PhD in Statistics preferred.

Hours & Work Schedule: 3 days in the office/2 remote

• Hours per Week: 40
• Work Schedule: Monday-Friday