As a Strategic Analytics Associate within the Risk Team, you will generate insightful analytics and provide recommendations concerning strategy development, implementation, operational controls, and performance monitoring. Your role will require a deep understanding of the problem universe, data analysis to understand root causes, and the use of analytics to design and implement solutions. You will play a pivotal role in promoting end-to-end solutions that mitigate risk while balancing the minimization of revenue loss, operating costs, and customer impacts.
Job Responsibilities:
- Develop and Implement end-to-end strategies to mitigate the credit abuse loss
- Monitor strategies to identify emerging attacks and trends and make changes to strategies in response
- Perform large loss case review to identify opportunity in the gap
- Collaborate with Operation team to enhance the credit abuse treatment
- Collaborate with various stakeholders which includes operations, Business GMs, Credit risk team and broader partner in driving initiatives.
- Provide support to senior leadership by delivering actionable insights and identifying opportunities for improvement within fraud portfolios
Required Qualifications, Capabilities and Skills:
- BS degree and minimum 5 years Risk Management or other quantitative experience required
- Background in statistics, econometric, or other quantitative field required
- Advanced understanding of SAS, SAS Enterprise Miner, or other decision tree software
- Ability to query large amounts of data and transform the raw data into actionable management information
- Familiarity with risk analytic techniques
- Strong analytical and problem-solving abilities
- Strong written and oral communication skills
- Experience delivering recommendations to management
Preferred Qualifications, Capabilities and Skills:
- MS degree and 3 years Risk Management or other quantitative experience preferred
- Experience in credit cards or financial services or risk management is preferred
- Working knowledge of detection & mitigation practices for fraud preferred