Quantitative Systematic Trading Internship - Master's: Summer 2027

Susquehanna International Group; Hong Kong; On-site; HKD 200,000 - 300,000; Full time

Job summary

Join Susquehanna International Group in Hong Kong as a Quantitative Systematic Trading Intern, where you will model market behaviors and create trading strategies. This internship offers a comprehensive education program and mentorship, preparing you for a full-time role upon graduation.

Ideal candidates will have a Master’s degree in quantitative fields and proficiency in Python. They should thrive in a collaborative environment and possess strong analytical and strategic thinking skills.

Qualifications

• Pursuing a Master’s (in penultimate or final year) in fields like Mathematics, Physics, Statistics, etc.
• Experience in programming languages, particularly Python.
• Strong analytical skills and logical reasoning.

Responsibilities

• Model market behavior through probability theory and statistical analysis.
• Create execution strategies based on modelling ideas.
• Backtest strategies using historical data.
• Collaborate with various teams within the company.

Skills

Statistical analysis and machine learning

Python programming

C++ or other low-level languages

Analytical problem-solving

Strategic thinking

Clear communication

Education

Master’s in quantitative fields

Job description

Overview

As a Quantitative Systematic Trading Intern at Susquehanna, you will work on projects that model the work of our full‑time employees. You will also go through a comprehensive education program and interact with mentors who are at the top of their field, allowing you to build foundational knowledge in quantitative finance. You will have the opportunity to build alphas on an actual trading strategy. Successful intern candidates will participate in a U.S. based internship with full‑time placement in our Hong Kong office upon graduation. Visa sponsorship is available for this position.

What You Can Expect

• Modelling. Apply probability theory, statistical analysis, and machine learning techniques to predict market behavior and generate alphas.
• Execution. Create strategies to execute on modelling ideas under simulated competition.
• Evaluation. Backtest ideas using historical market data and revise strategies.
• Breadth. Explore all aspects of quant work and different areas of Susquehanna’s business.
• Education. Participate in a comprehensive education program and receive personalized mentorship from experienced professionals to accelerate your growth.
• Collaboration. Work in an open environment that allows you to collaborate with multiple teams and get exposure to different groups and parts of the business.

What We're Looking For

• Master’s (in penultimate or final year) in quantitative fields such as Mathematics, Physics, Statistics, Electrical Engineering, Computer Science, Operations Research, or Economics.
• Analytical problem-solvers with excellent logical reasoning and a passion for turning data into decisions.
• Clear communicators in a fast‑paced and highly collaborative environment.
• Programmers comfortable processing and analyzing large data sets in Python; experience with C++ (or another low‑level language) is a plus.
• Strategic thinkers with demonstrated interests in strategic games and/or competitive activities.
• Self‑motivated and quick to learn, thriving in a dynamic, fast‑moving environment.

About Susquehanna

Susquehanna is a global quantitative trading firm powered by scientific rigor, curiosity, and innovation. Our culture is intellectually driven and highly collaborative, bringing together researchers, engineers, and traders to design and deploy impactful strategies in our systematic trading environment. To meet the unique challenges of global markets, Susquehanna applies machine learning and advanced quantitative research to vast datasets in order to uncover actionable insights and build effective strategies. By uniting deep market expertise with cutting‑edge technology, we excel in solving complex problems and pushing boundaries together.