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Overview
At Susquehanna, quantitative systematic traders tackle challenging data and algorithmic problems that inform decision-making in global financial markets. Their work spans signal generation, execution, market microstructure, portfolio construction, risk management, simulation, and large-scale data analysis, drawing from a broad quantitative toolkit to build strategies that trade in live markets.
As a Quantitative Systematic Trading Intern, you'll gain experience that closely reflects the work of our full-time research teams while participating in a structured education program designed to accelerate your development. Through hands-on research, mentorship, and close collaboration with researchers, engineers, and traders, you'll explore open-ended questions, design experiments, develop quantitative models, and evaluate ideas through rigorous empirical analysis and backtesting.
Susquehanna's extensive proprietary datasets and large-scale computing infrastructure-including a rapidly growing cluster of thousands of high-end GPUs-support computationally intensive research, large-scale simulation, and rapid experimentation. Our teams work in small, highly collaborative teams where ideas are debated openly, evidence guides decisions, and promising research can quickly produce practical impact.
Your Internship Experience
Your internship begins with Core Curriculum, an immersive, interdisciplinary program where Your internship begins with Core Curriculum, an immersive, interdisciplinary program in which quantitative and machine learning researchers, traders, and software engineers learn together. You'll build a shared foundation in quantitative trading, programming, data analysis, mathematical modeling, and modern machine learning and AI tools before applying those concepts to real-world problems.
You'll spend the rest of the summer on the Blast Project-an end-to-end simulation of quantitative work at Susquehanna. You'll research and develop a model, turn it into a trading strategy, and run that strategy against high-fidelity historical market data. Each day, you'll receive measurable feedback on its performance, allowing you to test hypotheses, refine your approach, and iterate rapidly-much as our research and trading teams do.
The project is deliberately broad. Rather than exposing you to just one narrow aspect of the job, it takes you through data analysis, modeling, implementation, simulated execution, evaluation, and the judgment calls in between. That breadth leads to continuous, engaging conversations among interns and mentors-and helps make the Blast Project one of the most memorable parts of the summer.
The strategy is your own, but you won't develop it alone. You'll be paired with a mentor from our research and trading staff, supported by dedicated teaching assistants, and surrounded by a cohort of interns working through the same challenge.
What we're looking for
We're looking for intellectually curious problem-solvers who are energized by difficult quantitative problems and motivated by rigorous experimentation.
You may be a strong fit if you have:

• A PhD in progress and expect to be in your penultimate or final year as of summer 2027, or currently a postdoctoral researcher, in computer science, economics, electrical engineering, mathematics, operations research, physics, statistics, or another highly quantitative discipline
• A strong foundation in probability, statistics, optimization, numerical methods, or quantitative modeling
• Experience developing research code in Python and working with large datasets; experience with C++, scientific computing, or high-performance computing is a plus
• Excellent problem-solving skills and an interest in using quantitative models to understand complex systems
• Strong communication skills and an interest in collaborating with researchers, engineers, and traders to refine ideas through discussion and experimentation
• A track record of intellectual curiosity demonstrated through academic research, competitions, strategic games, or other analytical pursuits
• The ability to thrive in an environment that values creativity, evidence-based thinking, collaboration, and continuous learning

By applying to this role, you will be automatically considered for the Quantitative Research Internship. There is no need to apply to both positions to be considered for both.
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.
If you're a recruiting agency and want to partner with us, please reach out to recruiting@sig.com. Any resume or referral submitted in the absence of a signed agreement will not be eligible for an agency fee.
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