Description

Lead quantitative analysis and develop statistical models to forecast balance sheets for bank stress testing.

This role is hybrid.

Responsibilities

• Develop and implement statistical models to forecast loan or deposit balances using macroeconomic relationships.
• Design, plan, and test modeling initiatives and cross-functional projects.
• Analyze large data sets to conduct applied research and streamline existing processes.
• Defend models and present findings to stakeholders, including business leaders and validation committees.
• Write and maintain code and documentation for all modeling functions.

Required Skills

• 7+ years developing and deploying predictive models, including traditional regression and machine learning.
• Proficiency in SAS and Python programming.
• Deep knowledge of financial services, specifically commercial and retail lending.
• Experience with stress testing frameworks such as CCAR and DFAST.
• Understanding of model governance and compliance standards.
• Ability to conduct applied research and define technical requirements to solve business problems.

Preferred Skills

• Experience working in Unix/Linux and Microsoft Azure environments.
• Proficiency with relational databases, SQL, and big data manipulation.

Key Skills

Education

Any Graduate