Quantitative Researcher - PhD: 2027
Susquehanna International Group LLP
Overview At Susquehanna, quantitative researchers tackle challenging data and algorithmic problems that inform decision-making in global financial markets. Their work spans statistical inference, optimization, market microstructure, simulation, forecasting, and large-scale data analysis, drawing on a broad quantitative toolkit to develop new insights and approaches As a Quantitative Researcher, you'll blend strong research capabilities with a deep understanding of trading to design, validate, backtest, and implement statistical and advanced machine learning models. Your work will span large-scale data analysis, alpha signal research, and strategy performance enhancement. While there is some overlap with the Quantitative Systematic Trader role, quantitative researchers typically focus more on model development, robustness, and long-term reliability. You'll have access to 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. Researchers work in small, highly collaborative teams where ideas are debated openly, evidence guides decisions, and promising research can quickly produce practical impact. What You Can Expect
- Modelling: Apply probability theory, statistical analysis, and machine learning techniques to build robust models and generate alphas
- Execution: Propose improvements to existing strategies and optimize how they perform in production
- Evaluation: Backtest ideas using historical market data and large-scale research clusters
- Education: Participate in a comprehensive education program and receive personalized mentorship from senior professionals to accelerate your growth
- Collaboration: Work in an open environment where you'll collaborate with systematic traders and technologists to push strategies into production
- A PhD, graduating by Summer 2027, or postdoctoral experience 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 research, competitions, strategic games, or other analytical pursuits
- The ability to thrive in an environment that values creativity, evidence-based thinking, and continuous learning
Vacancy posted 1 day ago
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