Intern Quantitative Risk Modeler Jobs in Mundelein, IL

Join J.P. Morgan Wealth Management's Exposure Management & Risk Analytics team and help shape how we measure, assess, and manage market and credit risk for our growing US Wealth Management business. You'll work alongside experienced risk professionals to develop innovative analytics, advance risk management capabilities, and deliver meaningful business impact. We offer a collaborative environment, opportunities for career growth, and the ability to contribute to high-visibility initiatives that influence risk strategy and decision-making.

As a Vice President within the Exposure Management & Risk Analytics team, you will develop and enhance risk analytics that support the assessment and management of market and credit risk across the US Wealth Management business. You will build and maintain quantitative models, stress testing frameworks, and production analytics that inform risk decisions and reporting. Working closely with risk, data, and reporting partners, you will help ensure analytics are scalable, controlled, and aligned with business and regulatory requirements. You will provide risk expertise to stakeholders and contribute to ongoing automation and process improvement initiatives. This role offers the opportunity to expand your technical and risk management expertise while influencing key business outcomes.

• Build and maintain stress testing, margin analytics, and risk modeling solutions using Python and SQL, leveraging internally developed models and workflows.
• Manage the production delivery and ongoing support of analytics infrastructure, including scheduling, monitoring, incident management, and controlled releases.
• Enforce production controls through version management, code reviews, testing, data quality validation, documentation, and change management practices.
• Execute quantitative modeling initiatives and translate market and risk insights into scalable analytics solutions.
• Enhance portfolio stress testing frameworks and perform scenario analyses to assess market and credit risk exposures.
• Develop and improve margin requirement analytics, including concentration, liquidity, volatility, and derivatives-related risk assessments.
• Apply regulatory margin frameworks and maintain governance, documentation, and regulatory alignment of analytical models.
• Provide market and margin risk expertise to business and partner teams by reviewing methodologies, controls, and risk assumptions.
• Partner with Data, Reporting, and Risk Monitoring teams to support risk analytics, reporting, and data pipeline requirements.
• Implement automation solutions that improve risk analysis, operational efficiency, and reporting capabilities.
• Deliver analytical insights and recommendations to support risk management decision-making.

• Minimum 5 years of experience in financial services, risk management, quantitative analysis, or a related technical field.
• Experience developing, deploying, and supporting analytics solutions within a production environment.
• Advanced proficiency in Python and SQL for data analysis, modeling, and automation.
• Knowledge of market risk concepts, including volatility, concentration risk, derivatives risk, and stress testing methodologies.
• Experience conducting quantitative analysis and developing risk analytics or modeling solutions.
• Knowledge of US Wealth Management products and related risk management practices.
• Familiarity with Regulation T and Portfolio Margin frameworks.
• Experience implementing controls related to code development, testing, validation, and documentation.
• Experience working with cross-functional stakeholders to support analytical and business objectives.
• Ability to communicate quantitative concepts and analytical findings to technical and non-technical audiences.
• Series 7 license or the ability to obtain the license within 120 days

• Experience developing or enhancing risk analytics methodologies and frameworks.
• Knowledge of financial mathematics, derivatives, options, or quantitative risk management techniques.
• Experience supporting stress testing, scenario analysis, or portfolio risk assessment programs.
• Familiarity with data science, machine learning, or advanced analytics techniques.
• Experience preparing methodology, validation, or model governance documentation.
• Knowledge of margin lending products and securities-based lending risk management practices.
• Experience collaborating with risk, technology, and data teams on analytical initiatives.