Quantitative Analytics Program Risk Analytics and Decision Science PhD Early Careers
You will apply advanced analytics, artificial intelligence, and machine learning to complex business challenges through a 12-month development program. You will complete two six-month rotations, develop and evaluate quantitative solutions, work with large datasets, design and deploy models, and apply statistical techniques to support credit risk, financial crime, customer experience, and operations.
Responsibilities
- Forecast loss and revenue for credit card loan portfolios
- Develop credit scorecards for consumer decisioning strategies
- Build models to identify money laundering patterns across transaction databases
- Predict operational losses using statistical and machine learning modeling
- Validate model design, calibration, and implementation
- Design and deploy models for credit risk, financial crime, customer experience, and operations
- Apply quantitative techniques to analyze large datasets and generate insights
Requirements
- 2+ years of quantitative analytics experience or equivalent experience, training, military experience, or education
- Master's degree or higher in statistics, mathematics, physics, engineering, computer science, economics, or a quantitative discipline
- Currently pursuing a PhD with expected graduation between December 2026 and June 2027, or completing a postdoc after graduating from a PhD program after May 2024
- Programming skills with Python, R, SQL, Spark, and Java
- Quantitative and analytical skills
- Data analysis, modeling, visualization, statistics, research, and generative AI experience
- Data and software engineering skills
- Data management skills
- Communication skills
- Business acumen and understanding of capital markets
- Risk assessment and risk control experience
- Knowledge of machine learning and AI models, statistical modeling, data management, and computing