Susquehanna is looking to solve the problem of building and refining data-driven, fully automated trading strategies to optimize profitability
Requirements
- PhDs graduating by Summer 2026 or postdocs in quantitative fields such as Mathematics, Physics, Statistics, Electrical Engineering, Computer Science, Operations Research, or Economics
- Programmers comfortable processing and analyzing large data sets in Python
- Experience with C++ (or another low-level language) is a plus
- Analytical problem-solvers with excellent logical reasoning and a passion for turning data into decisions
- Strong Trading Interest and drive to develop a deep mental model of microstructure and market intuition
- Strategic thinkers with demonstrated interests in strategic games and/or competitive activities
- Self-motivated and quick to learn, thriving in dynamic, fast-moving environment
Responsibilities
- Modelling. Apply probability theory, statistical analysis, and machine learning techniques to analyze and interpret market behavior
- Alpha Monetization. Blend quantitative signals with trading intuition and live market insights to optimize existing strategies or build new ones from the ground up
- Risk Management. Oversee the deployment and real-time operation of trading strategies, fine-tune parameters, and respond to anomalies as needed
- Collaboration. Work in an open environment that allows you to collaborate with researchers and technologists to build parts of the execution engine
- Apply quantitative research expertise with deep trading intuition to build and refine data-driven, fully automated trading strategies
- Actively monitor real-time strategy performance and use market behavior and feedback to improve and optimize profitability
- Participate in a comprehensive education program and receive personalized mentorship from senior professionals to accelerate your growth
Other
- Clear communicators in a fast-paced and highly collaborative environment
- Visa sponsorship is available for this position
- PhD degree in quantitative fields
- Strong collaboration and teamwork skills
- Ability to work in a dynamic, fast-moving environment
