Systematic Trading Quant Research Intern (Summer NYC)

Jain Global

New York (NY)

On-site

USD 182,000 - 234,000

Full time

26 hours ago
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Job summary

Jain Global, a multi-strategy investment firm, seeks a Quant Research Intern for Summer 2027 in New York. You will work at the intersection of quantitative research, technology, and markets, building data-driven trading strategies and scalable systems with portfolio managers, researchers, and technologists.

The internship emphasizes data analysis, model development, and systematic investment approaches, requiring strong analytical and programming skills and passion for quantitative methods in

Qualifications

  • Pursuing a Master’s or Ph.D. in a technical field related to ML or quantitative finance.
  • Strong programming skills in Python or similar languages.
  • Solid understanding of statistical modeling and data analysis.

Responsibilities

  • Assist in collecting, cleaning, and managing large financial datasets.
  • Develop and test quantitative models for pricing, forecasting, and trading.
  • Collaborate with researchers and developers on systematic trading strategies.
  • Contribute to process improvements to enhance efficiency and reduce risk.
  • Apply programming and analytical skills to solve problems in a fast-paced environment.
  • Communicate findings clearly to team members.

Skills

Python
Machine Learning
Statistical modeling
Data analysis
Teamwork
Communication

Education

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

Job description

Jain Global, a multi-strategy investment firm, seeks a Quant Research Intern for Summer 2027 in New York. You will work at the intersection of quantitative research, technology, and markets, building data-driven trading strategies and scalable systems with portfolio managers, researchers, and technologists.

The internship emphasizes data analysis, model development, and systematic investment approaches, requiring strong analytical and programming skills and passion for quantitative methods in

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