Description

You will execute monthly stress testing exercises to monitor risk appetite and identify vulnerable areas.

This role is on-site.

Responsibilities

• Execute monthly stress testing exercises, covering rapid stress testing processes and overlays.
• Build analytical tools to support outcome analysis, loss forecasting, and what-if scenarios.
• Gather and analyze portfolio and macro-economic data to assess business impact and integrate trends into loss forecasts.
• Partner with business units and risk managers to evaluate data availability and modeling approaches.
• Refine model performance monitoring processes to interpret outputs and identify improvements.

Required Skills

• 5+ years of experience in stress testing (CCAR/DFAST), CECL, or loss forecast model development.
• 5+ years of experience using Python or R for data analytics.
• Experience building analytical tools using Tableau, Excel, R Shiny, or Python.
• Knowledge of scenario design, sensitivity shocks, and risk identification processes.
• Quantitative skills to perform risk/reward trade-off analysis and derive patterns from data.
• Proficiency with MS Office Suite, including Word, Excel, and PowerPoint.
• Bachelor’s/University degree in Economics, Finance, or a quantitative major (Master's preferred).

Preferred Skills

• Experience with C&I and CRE loss forecast modeling analytics.
• Knowledge of PD/LGD/EAD models and experience in HFS/FVO.

Key Skills

Education

Bachelor’s/University degree