Quantitative Trading & Research Associate - 3-6 Months

JPMorganChase; Singapore; On-site; SGD 28,000 - 45,000; Full time

Job summary

JPMorgan Chase is seeking innovative problem-solvers for a 3- to 6-month Quantitative Trading & Research internship in Singapore. You will build mathematical models, gain exposure to risk modeling and investment banking, and work on hands-on projects with mentorship and a speaker series.

During the program, you will develop pricing, hedging, and risk measurement models for derivatives, apply machine learning, and contribute to analytics frameworks used across trading teams.

Qualifications

• Expected graduation beyond December 2027.
• Currently pursuing a Ph.D. in a quantitative field (e.g., Mathematics, Physics, Engineering, Computer Science, Machine Learning, Statistics).
• Proficiency in at least one programming language (e.g., Python, Java, JavaScript, C++, C#).
• You demonstrate quantitative and problem-solving skills as well as research ability.
• You are good at communicating concepts and ideas, both verbally and via documentation, and explain technical concepts to non-technical audiences.

Responsibilities

• As an associate in Quantitative Trading & Research (QTR), you will get exposure across Derivatives Pricing, Risk Management & Electronic Execution and Systematic, Data‑Driven Trading Analytics teams that drive innovation and process optimization using machine learning across sales/client engagement, risk, portfolio optimization, and electronic trading/market making.

Skills

Programming languages

Quantitative problem solving

Communication skills

Education

PhD in quantitative field

Tools

Python

Job description

JPMorgan Chase is seeking innovative problem-solvers for a 3- to 6-month Quantitative Trading & Research internship in Singapore. You will build mathematical models, gain exposure to risk modeling and investment banking, and work on hands-on projects with mentorship and a speaker series.

During the program, you will develop pricing, hedging, and risk measurement models for derivatives, apply machine learning, and contribute to analytics frameworks used across trading teams.