Quantitative Analytics Program, Risk Analytics and Decision Science

What you'll do

• Apply advanced analytics, artificial intelligence, and machine learning to solve complex business challenges.
• Develop and evaluate innovative solutions for risk management, customer experience, and business strategy.
• Forecast loss and revenue for credit card loan portfolios.
• Build models to identify money laundering patterns across large transaction databases.
• Predict operational losses using statistical and machine learning modeling techniques.
• Apply quantitative methods to validate model design, calibration, and implementation.
• Design and deploy scalable models for credit risk, financial crime, and underwriting.
• Translate sophisticated quantitative techniques into actionable insights for senior leadership.

What we're looking for

• Must have 6+ months of work experience or equivalent training/education.
• Currently pursuing a Master's degree in a quantitative field like Statistics, Data Science, or Computer Science (preferred).
• Expected graduation date between December 2026 and June 2027 (preferred).
• Excellent programming skills using Python, R, SQL, Spark, and Java (preferred).
• Strong quantitative skills to apply data analysis, modeling, visualization, statistics, research, and generative AI (preferred).
• Ability to use software engineering skills to design and deliver scalable solutions with an enterprise mindset (preferred).
• Experience in machine learning, AI models, statistical modeling, or data management (preferred).