Campus Quantitative Trader (Intern)

jumptrading; Singapore; On-site; SGD 22,000 - 33,000; Part time

Job summary

Jump Trading Group is offering a 10-week quant trading internship in Singapore. You will be embedded with trading teams as a quant trader/researcher/developer blend, receiving daily mentorship from experienced professionals and exposure to trading strategies, market mechanics, statistics, and research processes for signal generation.

The program emphasizes rigorous probabilistic thinking, mathematical reasoning, and programming experience, with hands-on projects and mock trading sessions to

Qualifications

• Outstanding skills in probabilistic thinking and mathematical reasoning.
• Competitive spirit and uncommon drive to learn and improve.
• Programming experience.
• Demonstrated interest in financial markets.
• Reliable and predictable availability required.

Responsibilities

• Internship focuses on trading aptitude and market understanding.
• Work on meaningful projects with daily mentorship.
• Participate in mock trading sessions and skill-building modules.
• Other duties as assigned.

Skills

Probabilistic thinking

Mathematical reasoning

Programming experience

Education

Undergraduate or graduate program

Tools

Python

Job description

Jump Trading Group is committed to world class research. We empower exceptional talents in Mathematics, Physics, and Computer Science to seek scientific boundaries, push through them, and apply cutting edge research to global financial markets. Our culture is unique. Constant innovation requires fearlessness, creativity, intellectual honesty, and a relentless competitive streak. We believe in winning together and unlocking unique individual talent by incentivizing collaboration and mutual respect. At Jump, research outcomes drive more than superior risk adjusted returns. We design, develop, and deploy technologies that change our world, fund start-ups across industries, and partner with leading global research organizations and universities to solve problems.

Our trading teams are each comprised of a dynamic group of traders, quantitative researchers, and engineers who work together to examine the global markets, seeking to understand the complexities of various traded products and exchanges. They leverage their impeccable statistical analysis and data mining skills, using the results of their research to make forecasts and develop profitable predictive trading models.

• Candidates should be interested in working in Singapore for their full-time job after graduation.
• Timing of application consideration and interviews will vary to accommodate university timelines.

About the Role:

The quant trading internship is an intensive 10-week program focused on enhancing your trading aptitude and understanding of financial markets, as well as helping you experience what it's like to be a full-time quant trader at Jump.

At Jump, our people contribute to trading teams in the following roles, or a blend of all three: quant trader, quant researcher, and quant developer. During our internship you will get training in all of these areas, with a focus in trading and financial markets. Topics include trading strategies and intuition, market mechanics, statistics, and our research process for signal generation.

You will have the opportunity to work with our trading teams on meaningful projects with real impact while receiving daily 1:1 mentorship from experienced quant traders, researchers, and developers. You will also participate in mock trading sessions, poker training, and other modules designed to improve probabilistic thinking, risk-taking, and trader mindset.

Other duties as assigned or needed.

Who Should Apply?

We are seeking the sharpest analytical minds from top undergraduate and graduate programs.

Ideal candidates will have:

• Outstanding skills in probabilistic thinking and mathematical reasoning
• Competitive spirit and uncommon drive to learn and improve
• Programming experience
• Appetite for risk-taking
• Demonstrated interest in financial markets
• Reliable and predictable availability required.