Job responsibilities

• Develop statistical and quantitative risk models for wholesale credit portfolios.

• Design, implement, and maintain JPMorgan Chase wholesale credit models, including stress testing and credit reserve requirements; support model backtesting and validation.

• Implement efficient numerical algorithms using Python and optimized C libraries.

• Build object-oriented software for risk analytics and integrate new models into the Firmwide Forecasting Framework.

• Analyze and debug unexpected forecast behaviors to improve accuracy and robustness.

• Conduct peer code reviews to elevate quality and performance of the forecasting framework.

• Collaborate with model developers and business partners to implement, test, and operationalize forecasting capabilities.

• Present progress, findings, and roadmap updates to senior leaders and modeling teams.

• Manage project deliverables, defect remediation, and new feature releases across model development cycles.

• Review, implement, and test technical documentation to ensure clarity and compliance.

Required qualifications, capabilities, and skills

• Bachelor’s degree or equivalent education in computer science, data science, mathematics, statistics, financial engineering, or related fields.

• Proficiency in object-oriented programming using C++ and Python.

• Strong knowledge of tools and methods for exploratory data analysis, such as Pandas and Num Py, which leverage efficient low-level C implementations.

• Experience with statistical modeling and Monte Carlo simulation.

• Ability to work with large datasets.

• Experience designing and consuming RESTful APIs for quantitative workflows (credit data, risk calculators, model executions).

Preferred qualifications, capabilities, and skills

• Experience with LLMs, prompt engineering, and AI-based agent coding tools is a plus.