JPMorgan Quantitative Modeling Lead 

India, Karnataka, Bengaluru 

997263452

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