Summer Intern - Quantitative Risk Management

OCC•Chicago, IL

3d•Hybrid

About The Position

The Options Clearing Corporation (OCC) is seeking interns for its Summer Internship Program, a 12-week opportunity running from May through August or June through September. This program is open to undergraduate and graduate students actively enrolled in a college or university. Interns will work up to 40 hours per week in a hybrid work environment, with overtime not permitted. The internship focuses on contributing to meaningful projects, applying skills to real business challenges, and making an impact on the future of OCC. The Quantitative Risk Management (QRM) team develops, validates, and maintains risk models for margin, clearing fund, and stress testing. Interns will support ongoing model development and monitoring efforts, gaining exposure to model evaluation, challenge, and maintenance in a central counterparty clearing environment.

Requirements

Rising senior or second-year graduate student, graduating December 2027 or May/August 2028.
Financial Mathematics, Financial Engineering, Statistics, Applied Mathematics, Finance, Economics majors desired.
Financial mathematics (derivatives pricing models, stochastic calculus, statistics and probability theory, advanced linear algebra).
Econometrics, data analysis and machine learning techniques.
Risk management Models.
Financial products knowledge: good understanding of markets and financial derivatives.
Basic programming skills: able to read and/or write code using a programming language (e.g., Python) in a collaborative software development setting.
Problem-solving skills: be able to identify a problem's possible source, conduct study and provide reasoning in estimating severity and impact.
Experience in office technology such as PowerPoint, Word, and Excel.

Nice To Haves

CFA, FRM are not required but preferred

Responsibilities

Assist in the model specification development and impact analysis.
Work on PNL decomposition and backtesting exceedance attribution analysis.
Work on model performance monitoring enhancements.
Support other BAU or / and R&D research projects such as supporting model annual validation, model performance monitoring, and parameter and assumption review.