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 NumPy, 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.