AI Intern

What you'll do

• Develop predictive AI and machine learning models to support portfolio risk analysis and business decision-making.
• Build Early Warning Vintage Monitoring models to improve loss forecasting and proactive risk detection.
• Develop forecasting and planning models to enhance lifetime loss projections and net credit loss forecasts.
• Perform data quality assessments, feature engineering, and analysis of large datasets to identify risk indicators.
• Translate portfolio behavior into actionable model features and business insights for Risk, Operations, and Technology teams.
• Present project outcomes, recommendations, and analytical findings to business stakeholders and senior leadership.

What we're looking for

• Must be currently enrolled in an undergraduate or graduate degree program in a relevant field like Data Science or Computer Science.
• Must be entering a Junior or Senior year of study at the start of the upcoming academic term.
• Must have a GPA of 3.0 or above.
• Must be able to perform work onsite in Dallas, TX or Franklin, TN.
• Must be legally authorized to work in the United States.
• Must have strong experience with Python, SQL, scikit-learn, XGBoost, and statistical modeling techniques.
• Must have experience with data quality analysis, feature engineering, and working with large datasets.
• Must have knowledge of model validation, back-testing, bias and fairness assessments, drift monitoring, and model explainability techniques.
• Experience with cloud and data platforms such as Snowflake or AWS (preferred).
• Exposure to predictive analytics, machine learning, and AI applications in financial services (preferred).
• Experience developing risk models, forecasting solutions, or analytical tools using large-scale datasets (preferred).
• Ability to translate complex analytical findings into clear business recommendations (preferred).