Description

You will lead quantitative analysis and develop statistical models to forecast balance sheets for bank stress testing.

Responsibilities

• Develop, implement, and execute statistical models to forecast loan or deposit balances using macroeconomic relationships.
• Lead the design, planning, implementation, and testing of modeling initiatives and cross-functional projects.
• Analyze and manipulate 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 robust code and well-articulated documentation for all modeling functions.

Required Skills

• 7+ years of experience 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.
• Strong written and verbal communication skills for stakeholder presentations.

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