Job Responsibilities:
- Design and implement vision, strategy, methodology and process for Risk strategies including appropriate measurement, evaluation and reporting standards are maintained within strategies to ensure the identification of risks and opportunities.
- Set adequate and measurable goals and objectives that ensure all tasks are carried out with a high degree of professionalism.
- Provide clear, concise and objective guidance to senior management and on risk issues in strategic decision making and help guide management to with a global view of risk including comprehensive summary reports to the appropriate committees
- Identify and implement world-class Card Risk Acquisition strategies while ensuring that all aspects of credit, legal, reputational and operational risks are considered.
- Monitor performance of Card Risk Acquisition strategies for relevant products.
- Develop deep and productive working relationship with the leaders across Marketing, Finance, Risk Execution, Legal and Compliance to identify opportunities to manage risk-adjusted returns for achieving financial and strategic objectives.
- Be an effective advocate and spokesperson for management on risk issues and risk management strategies.
Required qualifications, capabilities and skills:
- 7+ years of risk management or financial services experience
- Bachelor’s Degree with concentrations in Math, Finance, Statistics, Economics
- Strong written and verbal communication skills
- Data mining skills, specifically: SAS, SQL, Python, Excel, Microsoft Office, and database software applications
- Strong understanding or working knowledge of Credit Risk Models
- Flexible and able to handle multiple tasks and a changing environment
- Demonstrated experience in applying analytics to solve business problems efficiently and pragmatically through structured problem-solving approaches and proven independent decision-making skills
Preferred qualifications, capabilities and skills:
- Advanced degree preferred
- Working knowledge of Credit Risk Models including Machine Learning and Logistic regression models preferred