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Risk Management - Corporate - Wholesale Credit Risk Forecasting - Vice President
lead · Corporate Finance
About Wholesale Credit Risk – Forecasting
The WCR Product/Forecasting organization is an expert model, data, product-oriented group in J.P. Morgan, and a leader in financial engineering, data analytics, statistical modeling, and portfolio management. As a global team, Wholesale Credit Risk Forecasting works with quantitative research partners, risk managers and lines of businesses across all products and regions on strategic innovation, inventory and portfolio optimization, and governance of appropriate financial risk controls.
Opportunity
The successful Vice President candidate will join the Wholesale Credit Risk Forecasting Team, focused on data sourcing and analytics, delivering credit risk modeling and credit risk strategic innovation for the technology platforms to meet the requirements of CCAR/Stress Testing, and Credit Stress Framework, and Economic Credit Capital. You will play a leading role in monthly/quarterly model preparation and execution, as well as collaborate closely with lines of business, modelers and technology to design and implement strategic enhancements to wholesale credit projects including technology platform, operating model, data pipeline, and analytics framework. Additionally, with a strong commitment to scalability, resiliency, and stability, you will collaborate closely with cross-functional teams to deliver high-quality products that exceed customer expectations.
Specific responsibilities include:
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Execute and deliver the quarterly stress and allowance forecasting results with focus on data needs
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Collaborate and support the strategic build-out of stress testing workflow/dataflow for future initiatives
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Liaise with partners and LOBs to improve and enhance the forecasting process
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Perform control and reconciliation against deliveries in addition to creating/enhancing formal governance
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Navigate through database and data systems to perform data analysis, segmentation, transformation to prepare various datasets
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Design and develop tools (Python/SQL/Tableau/AI based) to automate data sourcing/analytical processes that assess data quality, data completeness, and readiness for forecasting
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Understand the implementation of the forecasting regression models and how they use data for forecasting
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Understand the implementation of the forecasting architecture, systems and dataflow
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Identify issues and streamline data flow from acquisition to results production
The ideal candidate should possess the following:
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BA/BS degree in computers, mathematics, finance or a related field
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Minimum of 5 years of experience working in a finance organization with data analytics and/or credit risk; knowledge of CCAR/Economic Capital/Stress Testing/Basel in Wholesale Credit Commercial & Industrial and/or commercial real estate is preferred but not required
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Ability to organize work and solve problems independently and excel in a deadline-oriented environment
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Strong communications skills, written and verbal – significant interaction with LOBs, risk streams, senior managers, and external stakeholders
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Technologically savvy with an ability to understand systems and their internal functionality; Coding knowledge and experience in Python/SQL is desirable but not required
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Understanding of big-data analytics and strategic data synthesis is desirable
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Proactive, self-starter with ability to work in a collaborative environment
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Tableau and data visualization familiarity preferred