Quantitative Researcher - PhD: 2027

OverviewAt 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 approachesAs 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 ExpectModelling: Apply probability theory, statistical analysis, and machine learning techniques to build robust models and generate alphasExecution: Propose improvements to existing strategies and optimize how they perform in productionEvaluation: Backtest ideas using historical market data and large-scale research clustersEducation: Participate in a comprehensive education program and receive personalized mentorship from senior professionals to accelerate your growthCollaboration: Work in an open environment where you’ll collaborate with systematic traders and technologists to push strategies into productionWhat we’re looking forWe’re looking for intellectually curious researchers who are energized by difficult quantitative problems and motivated by rigorous experimentation.You may be a strong fit if you have:A PhD, graduating by Summer 2027, or postdoctoral experience in computer science, economics, electrical engineering, mathematics, operations research, physics, statistics, or another highly quantitative disciplineA strong foundation in probability, statistics, optimization, numerical methods, or quantitative modelingExperience developing research code in Python and working with large datasets; experience with C++, scientific computing, or high-performance computing is a plusExcellent problem-solving skills and an interest in using quantitative models to understand complex systemsStrong communication skills and an interest in collaborating with researchers, engineers, and traders to refine ideas through discussion and experimentationA track record of intellectual curiosity demonstrated through research, competitions, strategic games, or other analytical pursuitsThe ability to thrive in an environment that values creativity, evidence-based thinking, and continuous learningVisa sponsorship is available for this position.By applying to this role, you will be automatically considered for the Quantitative Systematic Trader position. There is no need to apply to both positions to be considered for both.About SusquehannaSusquehanna 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 View email address on click.appcast.io. Any resume or referral submitted in the absence of a signed agreement will not be eligible for an agency fee.#LI-CR1#LI-OnsiteJob SummaryExperience Level: New GraduatesJob Categories: Quantitative Research