Quantitative Trading Intern — AI & Data Systems

Jain Global; New York (NY); On-site; USD 182,000 - 234,000; Full time

Job summary

Jain Global seeks a Quantitative Developer Intern to join our Technology and Research team in New York. You will contribute to the development of advanced trading systems and analytical frameworks at the intersection of quantitative research, technology, and financial markets.

You will gain hands-on experience in data analysis, model implementation, and AI-driven systematic investment strategies while collaborating with portfolio managers, researchers, and technologists on real-world projects

Qualifications

• Pursuing a Master’s or Ph.D. in quantitative fields.
• Proficiency in Python or C++ with data structures and algorithms.
• Experience with AI tools and ML frameworks is a plus.

Responsibilities

• Design, develop, and optimize software tools, data pipelines, and research infrastructure to support trading and quantitative research.
• Apply strong computational and technical skills to problems at the intersection of trading and technology.
• Implement and evaluate ML/AI tools to enhance trading models, research workflows, and automation.
• Perform exploratory data analysis and statistical modeling on large, complex datasets to inform signal and strategy development.
• Support automation of data workflows and real-time analytics processes for production systems.
• Collaborate with researchers and engineers to backtest strategies, analyze performance, and deploy research insights into live environments.
• Contribute to the continuous improvement of system performance, scalability, and reliability.

Skills

Python

C++

Data structures

Algorithms

Statistical modeling

ML frameworks

Communication

Teamwork

Education

Master’s or Ph.D. in Computational Finance/Math/CS/Statistics/ML

Job description

Jain Global seeks a Quantitative Developer Intern to join our Technology and Research team in New York. You will contribute to the development of advanced trading systems and analytical frameworks at the intersection of quantitative research, technology, and financial markets.

You will gain hands-on experience in data analysis, model implementation, and AI-driven systematic investment strategies while collaborating with portfolio managers, researchers, and technologists on real-world projects