Card Loss Forecasting VP: Portfolio Risk & Insights

Testing Site - JPMC; Columbus (OH); On-site; USD 130,000 - 180,000; Full time

Job summary

JPMorgan Chase & Co. is seeking a seasoned Credit Loss Forecaster for the Card Loss Forecasting team within CCB Risk Management in Columbus, OH.

You will produce forecasts for the $220B credit card portfolio, deliver insights to senior leadership, and support budget planning and regulatory reporting. The role requires advanced analytic skills, 5+ years in credit risk, and proficiency with Python, SAS, and SQL.

Qualifications

• Bachelor's or Master's in a quantitative field such as Finance, Economics, Statistics, Math, or Engineering.
• Minimum 5 years in credit risk management, loss forecasting, modeling or related consulting.
• Minimum 7 years of related analytical experience.
• Proficiency in Excel and PowerPoint; strong data analysis skills.

Responsibilities

• Produce the credit card loss forecast for bank-wide budget across segments.
• Build and modify origination vintages and product-level forecasts.
• Analyze model outputs and translate results for leadership.
• Collaborate with Finance, Modeling and Risk Strategy to adjust portfolios.
• Create executive presentations and risk deep-dive summaries.
• Run sensitivity scenarios under different macro conditions.
• Support regulatory reporting and ad hoc analyses.
• Mentor junior analysts and guide risk management knowledge.

Skills

Credit risk analysis

Forecasting

Statistical modeling

Data interpretation

Communication skills

Leadership

Education

Bachelor's or Master's in Finance, Economics, Statistics, Math, or Engineering

Tools

Python

SAS

SQL

Job description

JPMorgan Chase & Co. is seeking a seasoned Credit Loss Forecaster for the Card Loss Forecasting team within CCB Risk Management in Columbus, OH.

You will produce forecasts for the $220B credit card portfolio, deliver insights to senior leadership, and support budget planning and regulatory reporting. The role requires advanced analytic skills, 5+ years in credit risk, and proficiency with Python, SAS, and SQL.