Risk Management -Wholesale Credit Risk… at JPMorganChase · 545…

Summary: JPMorgan Chase is a leading financial institution, and they are seeking a Wholesale Credit Risk Associate to design and implement modern risk modeling platforms and algorithms. The role involves collaborating with model developers and business stakeholders to translate complex analytics into scalable solutions while enhancing skills in quantitative modeling and software engineering. 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: - Master'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: - Experience with LLMs, prompt engineering, and AI-based agent coding tools is a plus Required Skills: Statistical modeling, Python, C++ Important Skills: Data analysis tools, RESTful APIs Nice-to-Have Skills: Monte Carlo simulation, Large datasets, LLMs, AI tools Benefits: Comprehensive health care coverage, On-site health and wellness centers, A retirement savings plan, Backup childcare, Tuition reimbursement, Mental health support, Financial coaching