Summer Intern, Supervision Regulation & Credit, Credit Lending Research

Federal Reserve System • Philadelphia, PA

10d • $23 - $28 • Hybrid

About The Position

The Federal Reserve Bank of Philadelphia is seeking a graduate or advanced undergraduate student with preferred majors in quantitative fields such as applied mathematics, statistics, economics, finance, or computer science. This opening requires the selected candidate to be in office four times a week with one day working remotely. The work schedule is Monday – Friday (40 hour per week). This is a 10-week paid internship. The hourly rate for this position is $23.00-$28.00 per hour depending on the candidate's education. The intern will complete a research project that studies how machine-learning, data mining, and Gen-AI analytical tools can support modeling of retail loan credit risk. More specifically, the intern will use these and other tools to test how delinquency and default in retail portfolios (such as credit cards, auto loans, or mortgage loans) are impacted by risk factors, such as borrower characteristics, loan characteristics, or the macroeconomic environment. The intern will be encouraged to explore non-linear relations and interactions identified by the models.

Requirements

• A rising junior or senior undergraduate, or master’s student pursuing a degree related to applied mathematics, statistics, economics, finance, or computer science. Other quantitative fields related to the ones listed are also encouraged to apply.
• Experience with statistical/programming software (experience with R or Python is preferred)
• Strong presentation and communication skills

Nice To Haves

• Strong technical writing skills
• Verbal and written communication skills
• Strong problem-solving skills
• Attention to detail
• Organizational skills
• Ability to work well independently with little supervision (the intern supervisor will be available to assist)

Responsibilities

• The intern will complete a research project that studies how machine-learning, data mining, and Gen-AI analytical tools can support modeling of retail loan credit risk.
• The intern will use these and other tools to test how delinquency and default in retail portfolios (such as credit cards, auto loans, or mortgage loans) are impacted by risk factors, such as borrower characteristics, loan characteristics, or the macroeconomic environment.
• The intern will be encouraged to explore non-linear relations and interactions identified by the models.

What This Job Offers

• Job Type: Part-time
• Career Level: Intern
• Number of Employees: 501-1,000 employees