Summer Intern - Quantitative Risk Management

The Model Performance Monitoring team is responsible for the ongoing monitoring, testing, and governance of the firm's risk models, ensuring model performance remains sound, well-documented, and compliant with regulatory expectations. ## Planned Responsibilities and Learning Objectives - Support model performance and backtesting exercises using historical portfolio data under the supervision of senior team members. - Contribute to Python scripting with Pandas for data processing and automation of monitoring workflows. - Assist with exploratory data analysis and visualization of model performance metrics using tools such as Tableau and Dash. - Review and help draft documentation for model monitoring metrics and testing procedures. - Participate in code reviews and team discussions on model monitoring best practices. ## Job Summary and Responsibilities - Perform model performance testing, including portfolio backtesting using historical data. - Implement model monitoring metrics, focusing on requirements coding and testing quality. - Write and review documentation for model monitoring metrics, prototypes, and implementation. - Support the launch of new products by enhancing monitoring capabilities. - Develop Python scripts with Pandas and object-oriented programming to automate data processing. - Assist analysts in solving their analytics questions and challenges. ## Candidate Qualifications Rising senior or second-year graduate student, graduating December 2027 or May/August 2028. ## Desired Majors Master's degree or equivalent in a quantitative field such as data analytics, computer science, mathematics, physics, finance, or financial engineering. ## Technical Skills and Experience Desired - Strong programming skills and ability to read or write Python code in a collaborative software development setting. - Experience with a source code repository system, preferably Git. - Ability to write and optimize complex analytical SQL queries. - Comfort supporting business analysts on high-priority projects. - Strong problem-solving skills, including the ability to identify a problem's source, severity, and impact and determine possible solutions and needed resources. - Experience with PowerPoint, Confluence, Word, and Excel. ## Additional Qualifications - Exposure to data orchestration tools such as Airflow. - Experience with Tableau, Dash, and Alteryx. - Understanding of applied statistics and hands-on experience applying statistical concepts. - Strong quantitative skills in financial mathematics, econometrics, data analysis, machine learning, numerical methods, optimization, Monte Carlo simulation, risk management methods, and financial products. ## Internship Details This is a seasonal 12-week summer 2027 internship for undergraduate and graduate students actively enrolled at a college or university. Interns work up to 40 hours per week in a hybrid work environment, and overtime is not permitted.