Lead Credit Risk Modeling & Forecasting Analyst

Synchrony; Stamford (CT); Hybrid; USD 85,000 - 140,000; Full time

Job summary

Synchrony’s Credit and Capital Management group seeks a data scientist and credit risk modeling professional to execute, maintain and develop CECL and related models under SR 11-7 / OCC guidelines. The role centers on quarterly reserve development, loss projections and strong governance.

You will use Python/Pandas, Spark, Hadoop, SQL and Linux, collaborate with IT, Finance and Controllership, produce robust analyses and documentation, and drive model enhancements and re-calibrations to reflect

Qualifications

• Bachelor’s degree with quantitative underpinning and 5+ years of experience in Programming / Analytics or 9+ years in Risk/Credit/Finance/Consumer Lending
• 5+ years’ experience programming in SQL, Python, Spark; proficient in Linux and large-scale data handling
• Willingness to travel for business as required

Responsibilities

• Plan and execute models in production Reserves and Loss Forecasting with CECL focus
• Maintain model data input monitoring, controls and output analytics with documentation
• Support quarterly reviews, governance, and peer review processes
• Visualize insights and trends for effective decisioning
• Communicate assumptions and projections to model owners and sponsors
• Assist with model validation responses and governance requests
• Support development of new models or enhancements to existing ones
• Manage models through lifecycle from development to production and calibration

Skills

Python

Pandas

Spark

SQL

Linux

Data analysis

Modeling

Education

Bachelor’s degree in a quantitative field

Tools

Hadoop

AWS

HDFS

Job description

Synchrony’s Credit and Capital Management group seeks a data scientist and credit risk modeling professional to execute, maintain and develop CECL and related models under SR 11-7 / OCC guidelines. The role centers on quarterly reserve development, loss projections and strong governance.

You will use Python/Pandas, Spark, Hadoop, SQL and Linux, collaborate with IT, Finance and Controllership, produce robust analyses and documentation, and drive model enhancements and re-calibrations to reflect