Modelling Analytics - Associate

As a professional within the Card Loss Forecasting team, you will be responsible for producing credit card delinquency and loss forecasts by portfolio segments and providing analytical insights to senior management. This role provides an exciting opportunity to develop your skills in a fast-paced environment. Financially, credit card represents the majority of Chase's consumer credit losses. As a result, forecasted credit card losses are a focus of senior leaders, regulators, and investors, as illustrated by the extensive coverage of card losses at Investor Day and quarterly earnings

In this role, you'll:

• Analyze & monitor internal & external risks impacting credit cards portfolio
• Produce the credit card loss forecast for bank-wide budget, including forecasts for several discrete segments including policy losses, bankruptcy, deceased and recoveries and reversals
• Build out, analyze and modify origination vintage and product level forecasts
• Analyze and understand loss forecasting quantitative model output
• Create PowerPoint and other summarizations for Executive Leadership
• Create and run sensitivity scenarios based on economic conditions and management direction
• Monitor and present delinquency forecasts to key line of business partners
• Create and validate regulatory reporting
• Provide insight for senior management via regular risk deep dives

Qualifications:

• A Bachelor's degree in a quantitative discipline (Finance/Stats/Econ/Math/Engineering) or equivalent work/training is required. Advanced degree preferred
• Minimum 3 years Credit Risk Management, Statistical Modeling, Marketing Analytics and/or Consulting experience
• Strong knowledge of Python, SAS, SQL and MS Office required
• Prior experience to credit forecasting or underwriting of unsecured lending products like credit card, personal loans or BNPL
• Strong analytical, interpretive, and problem solving skills with the ability to interpret large amounts of data and its impact in both operational and financial areas
• Excellent oral, written communication and presentation skills