Senior Credit Risk Modeling & Forecasting Analyst

Synchrony; Chicago, Northern (IL, KY); Hybrid; USD 85,000 - 140,000; Full time

Job summary

Synchrony is seeking a data scientist/credit risk modeling professional to execute, maintain, and develop models under SR 11-7, OCC guidance, CECL, CCAR, and DFAST. The role focuses on quarterly reserve development, loss forecasts, and governance across the Reserves & Loss Forecasting team.

The candidate will analyze trends across the Synchrony portfolio, collaborate with IT and model development, and communicate complex results to stakeholders while ensuring compliance with model risk

Qualifications

• Bachelor's degree with quantitative underpinning and 5+ years of experience in Programming/Analytics in Risk, Credit, Finance or related fields
• 5+ years’ experience with SQL, Python, Spark; strong data analysis and modeling skills; Linux experience
• Willingness to travel for business as required

Responsibilities

• Plan and execute models in the production Reserves and Loss Forecasting process focusing on CECL and related estimates
• Maintain model data input monitoring, production controls and output analytics with documentation
• Support quarterly review and quarter closing activities, contributing to governance and controls
• Visualize insights and trends in inputs/outputs for clear decisioning
• Explain drivers and provide narrative support for assumptions and projections to model owners
• Assist with model validation responses and ensure adherence to governance standards

Skills

SQL

Python

Spark

Linux

Hadoop

Education

Bachelor's degree in quantitative field

Tools

Pandas

Job description

Synchrony is seeking a data scientist/credit risk modeling professional to execute, maintain, and develop models under SR 11-7, OCC guidance, CECL, CCAR, and DFAST. The role focuses on quarterly reserve development, loss forecasts, and governance across the Reserves & Loss Forecasting team.

The candidate will analyze trends across the Synchrony portfolio, collaborate with IT and model development, and communicate complex results to stakeholders while ensuring compliance with model risk