Quant Research Intern - Risk & Treasury Modeling

JPMorganChase; Paris; Sur place; EUR 17 000 - 23 000; Plein temps

Résumé du poste

JPMorganChase invites applications for a Quantitative Research – Risk and Treasury off-cycle intern within the Quantitative Modeling Program in Paris. You will apply your academic knowledge to real-world financial challenges, gain hands-on experience, and build a valuable network, with potential full-time offers upon successful completion.

You will analyze data, backtest strategies, and contribute to model development across asset classes while collaborating with top-tier professionals in a

Qualifications

• Enrolled in a Master's program in mathematics, statistics, physics, engineering, computer science, economics, or data science/machine learning, graduating between September 2026 and March 2028.
• Proficiency in Python, and/or C++ programming.
• Strong modeling, analytical, quantitative, and problem-solving skills.
• Excellent communication skills for presenting complex concepts.

Responsabilités

• Analyze data to identify patterns and trends.
• Conduct back testing and assess strategies.
• Maintain and improve software systems and tools for risk and treasury operations.
• Assess models for conceptual soundness, risks, and enhancements.
• Propose creative solutions to complex challenges.
• Collaborate with internal teams to advance risk and treasury services.
• Focus on model development and review of conceptual design.
• Develop, validate, and enhance mathematical models and algorithms.
• Optimize financial solutions across asset classes and instruments.

Connaissances

Python

C++

Modeling

Analytical thinking

Communication

Banking analytics

Team collaboration

Formation

Master's degree in a relevant field

Outils

R

MATLAB

SQL

Description du poste

JPMorganChase invites applications for a Quantitative Research – Risk and Treasury off-cycle intern within the Quantitative Modeling Program in Paris. You will apply your academic knowledge to real-world financial challenges, gain hands-on experience, and build a valuable network, with potential full-time offers upon successful completion.

You will analyze data, backtest strategies, and contribute to model development across asset classes while collaborating with top-tier professionals in a