Bring your expertise to JPMorgan Chase. As part of Risk Management and Compliance, you are at the center of keeping JPMorgan Chase strong and resilient. You help the firm grow its business in a responsible way by anticipating new and emerging risks, and using your expert judgement to solve real-world challenges that impact our company, customers and communities. Our culture in Risk Management and Compliance is all about thinking outside the box, challenging the status quo and striving to be best-in-class.

As a Strategic Analytics Lead - Vice President in within our Consumer and Community Banking (CCB) Card Services Risk group, you will drive exposure management strategies to minimize portfolio losses balancing risk and rewards, with people management responsibilities leading a team of analysts and driving analytics.

Job Responsibilities

• Translate customer data into insights that drive lending exposure management strategies
• Develop actionable segmentation based on internal and external attributes to clearly identify opportunities for exposure management, drive targeting strategies, and measure overall portfolio performance
• Collaborate with partners in marketing, risk, lending operations and finance to assess credit card risk and exposure across key customer segments and align exposure management strategies to minimize portfolio losses balancing risk and reward
• Work with the Risk Analytics team to identify new lending tools and treatments to minimize portfolio losses while driving profitable growth with the appropriate risk strategies
• Forecast P&L impacts of various risk initiatives
• Measure strategy and campaign performance and communicate results and recommendations to senior leadership
• Lead a team of analysts to drive analytics and provide partner support

Required qualification's, capabilities and skills 

• Bachelor’s degree in Management, Information Systems, Data Science, or related field of study 
• Minimum 5 years of experience in Strategic Analysis, Business Analysis, Strategy and Analytics or similar quantitative area. 
• Experience in SQL/Python and Unix
• Statistical analysis tools such as SAS, SAS Enterprise Miner, Knowledgestudio or Alteryx languages to assemble and manipulate data and perform statistical analysis
• Machine learning techniques such as Decision Tree and Clustering
• Familiarity with Data platforms Oracle or Teradata 
• Familiarity in Credit Card P&L
• Proficient in Microsoft Excel