Quantitative Finance Analyst: Risk Models & Analytics

Bank of America; United States; Remote; USD 120,000 - 180,000; Full time

Job summary

Bank of America is seeking a Quantitative Finance Analyst to conduct quantitative analytics and modeling for the wholesale credit risk domain. You will develop loss forecasting, scorecards, and regulatory capital models, and communicate results to stakeholders.

This role requires an advanced degree, 5+ years in credit risk modeling, strong programming (R, Python, SQL), and experience with data architecture, large datasets, and production deployments.

Qualifications

• Master’s degree in a quantitative field is required.
• 5+ years professional experience developing credit risk models.
• Strong programming skills (R, Python, SAS, SQL).
• Ability to communicate complex quantitative topics to technical and non-technical audiences.

Responsibilities

• Perform end-to-end market risk stress testing including scenario design and reporting.
• Support model development and model risk management in focus areas.
• Analyze large datasets and interpret results using qualitative and quantitative methods.
• Develop wholesale credit risk models including loss forecasting and scorecards.
• Prepare white papers for developed models and communicate outcomes to stakeholders.
• Collaborate with internal model risk management and remediating findings.

Skills

Critical Thinking

Quantitative Development

Risk Analytics

Risk Modeling

Technical Documentation

Adaptability

Collaboration

Problem Solving

Risk Management

Data Modeling

Data and Trend Analysis

Process Performance Measurement

Research

Written Communications

Education

Master’s degree in Math, Economics, Statistics, Engineering, Finance, Computer Science or similar discipline

Tools

Hadoop

Alteryx

Tableau

MicroStrategy

LaTeX

Job description

Bank of America is seeking a Quantitative Finance Analyst to conduct quantitative analytics and modeling for the wholesale credit risk domain. You will develop loss forecasting, scorecards, and regulatory capital models, and communicate results to stakeholders.

This role requires an advanced degree, 5+ years in credit risk modeling, strong programming (R, Python, SQL), and experience with data architecture, large datasets, and production deployments.