Overview

Our CECL (Current Expected Credit Loss) Quantitative Modeling Team operates at the heart of the Lending Business unit, building accurate credit loss forecasting models through advanced statistical technique, and playing a pivotal role in ensuring the financial stability of Navy Federal Credit Union by informing CU leaders the right level of credit reserve recommendations. Our team's primary responsibility is to develop and implement advanced quantitative models that enable accurate assessments of potential credit losses across our lending portfolio.

The Summer Associate will work in a flexible hybrid manner and report to leadership at our Vienna, VA campus. Responsibilities will include analyzing data and participating in activities related to quantitative modeling. As part of the team, you will have the chance to work on real-world projects, collaborate with seasoned professionals, and contribute to impactful initiatives. You'll gain exposure to quantitative modeling techniques commonly employed by nation's largest financial institutions, and learn analytical skills applied to large financial data.

• Develop models to test and evaluate different modeling techniques
• Investigating and analyzing potential model performance-improving independent variables
• Analyzing model performance and understanding the cause of prediction errors
• Finding potential performance-improving changes to the existing models
• Model sensitivity analysis
• Analyzing portfolio shifting and its impacts
• Economic research relating to portfolio performance
• Automating modeling related activities using R or Python

• Perform data pull from source data systems and prepare data for analysis or model development
• Analyze data to understand its impact on model performance
• Participate in model development, model execution and model monitoring related activities
• Work with experienced modeling professionals within the team to support various initiatives
• Perform other ad hoc analysis
• Prepare reports of analytical findings

• Currently pursuing a master's or PhD degree in a quantitative field like statistics, computer science, data science, quantitative finance, or economics
• Experience with research, analysis, and data manipulation
• Experience using programming and analytic tools such as: Python, R, SQL, or Tableau
• Strong problem-solving, critical, and analytical thinking skills
• Good communication and presentation skills
• Comfort working with large datasets and understand the basic database concepts
• Ability to work independently and think outside of the box
• Basic knowledge of financial services/payments a plus