Job Description
Intern Project:
The intern will be working on a research project that studies how Machine Learning (ML) techniques can be used to predict credit performance for retail loans like auto, other consumer loans, or student loans using Equifax Consumer Credit Panel (CCP) data.
Project timeline:
Phase 1 (Weeks 1-2): Assemble training and test sample dataset using CCP auto, other loan and student loan tradelines
Phase 2 (Weeks 3-5): Perform the data cleaning and gain related knowledge of CCP tradeline data.
Phase 3 (Week 6): Deploy common linear model techniques like logistic regression models, and popular ML models to predict default of retail loans. Perform model performance comparison during GFC, Pandemic and other periods.
Phase 4 (Weeks 7-9): Identify areas where ML models can complement traditional linear models.
Phase 5 (Week 10): The intern will prepare a presentation on their findings and present this to interested RMR modelers andFRB as the capstone to this internship.
What You Have
PhD or graduate student studying economics, finance, statistics, applied mathematics, data analytics, computer science, orother related majors
Required Skills:
Familiar with popular ML packages provided in Python or R environment. Python is the preferred language
Some experience with handling large datasets
Preferred Competencies:
Excellent problem-solving and communication skills
Detail oriented and very organized about codes and documentation
Additional Information:
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