Quantitative Modeling Lead

THE TEAM

The Consumer and Community Banking (CCB) Portfolio Risk Modeling Center of Excellence consists of an intellectually diverse team of economists, statisticians, mathematicians, and other analytics professionals, focused on quantitative modeling of risks within the lending portfolios of the CCB businesses within JPMorgan Chase & Co. The team answers complex and unique questions, utilizing cutting edge quantitative methods and leverage one of the world’s largest repositories of consumer lending data. By applying expert knowledge in predictive modeling, along with a deep understanding of the businesses of consumer lending, we partner with teams across JPMC to assess, measure, and manage critical risks within the CCB consumer loan portfolios.

The Quantitative Modeling Lead will be a key member of the Portfolio Risk Modeling team. The successful candidate will be responsible for end-to-end model design and development. This position is a team leader and will have responsibilities of leading a team of professionals. The candidate will build a solid understanding of various consumer products and key risk drivers and use that to further enhance the models.

This opening is specific to the Auto and Business Banking Forecasting Model Development Team within Portfolio Risk Modeling.

THE POSITION
As an Vice President, you will be part of and lead a team of quantitative professionals developing and maintaining advanced credit risk forecasting models for assessment of CCB’s retail portfolios which are used for both regulatory and portfolio risk management purposes.

Responsibilities will include:

• Design, develop, test, and validate statistical/economic models for consumer/retail portfolios, including probability of default, loss given default, and exposure at default.
• Utilize state-of-the-art modeling including both classical statistical modeling approaches and modern machine learning approaches to enhance existing models and tackle challenging modeling problems
• Manage end-to-end model development process, including data manipulation, exploratory data analysis and pattern discovery, model development, refinement and validation, documentation, assisting with implementation, and performance monitoring
• Collaborate with cross functional partners in Risk, Finance, Technology, Model Governance throughout the entire modeling life cycle.

Qualifications

• Advanced degree in a quantitative discipline (e.g. Mathematics, Statistics, Economics, Computer Science, Operations Research) - Masters with 6+ years of relevant working experience or a PhD.
• Strong data analysis and statistical/economic modeling experience, such as generalized linear models, multivariate analysis and time series analysis
• Proficiency in advanced analytical languages (e.g. SAS, Python, R); Familiarity with framework of machine learning pipeline (e.g. tensor flow, scikit-learn) is not required but a plus
• Ability to work with large data and perform extensive analysis to draw useful insights
• Strong communication skills to present to and collaborate with business partners and model end-users Strong organizational and multi-tasking skills with demonstrated ability to manage expectations and deliver quality results on time
• Comfortable working both independently and in a team environment
• Credit risk modeling experience is a plus, but not necessary