Preferred Background •Major in CS, Data Science, AI/ML, or Engineering •Familiarity with Python and common ML libraries •Interest in applied AI, ML systems, or AI-enabled applications
Internship Description
This internship provides project-based learning exposure to risk modeling and analysis, focusing on credit and market risk concepts commonly used in financial institutions. Participants will work on guided risk analysis projects, learning how quantitative models support risk assessment and decision-making.
Activities & Exposure
• Gather and analyze risk-related datasets using Python or R
• Practice building stress-testing and Value-at-Risk (VaR) models
• Explore scenario analysis and risk metric dashboards
• Present risk analysis findings in structured reviews
Outcomes
• Practical understanding of risk modeling frameworks
• Experience translating quantitative results into insights
• Exposure to financial risk analysis workflows
Requirements
Preferred Background
Finance, Statistics, Economics, or Quantitative majors
Familiarity with regression, probability, and basic statistics
Experience with Excel and data visualization tools
Interest in risk management or quantitative finance