Federal Reserve Bank (FRB)
Summer Intern – Supervision & Regulation – Retail SMT Machine Learning (Manufacturing)
Bring your passion and expertise, and we'll provide the opportunities that will challenge you and propel your growth!
Job Summary:
The Federal Reserve Bank of Philadelphia is seeking a PhD level or graduate student with preferred majors in economics, finance, statistics, applied mathematics, data analytics, computer science, or any other related major. This opening is hybrid role. This position may be fully remote, though a hybrid model where the intern comes into the office 2-3 times a week to work with the project manager will also be permissible.
The work schedule is Monday – Friday (40 hour per week). This is a 10-week paid internship. The hourly rate for this position is $26.00-$30.00 per hour depending on the candidate's education.
What You Will Do
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 and FRB as the capstone to this internship.
What You Have
PhD or graduate student studying economics, finance, statistics, applied mathematics, data analytics, computer science, or other 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:
The Federal Reserve Banks are committed to equal employment opportunity for employees and job applicants in compliance with applicable law and to an environment where employees are valued for their differences.
Always verify and apply to jobs on Federal Reserve System Careers (https://rb.wd5.myworkdayjobs.com/FRS) or through verified Federal Reserve Bank social media channels.