Faculty Fellow

Susquehanna International Group, LLP • Bala Cynwyd (Philadelphia Area), PA

62d • Onsite

About The Position

At Susquehanna, we approach quantitative finance with a deep commitment to scientific rigor and innovation. Our research leverages vast and diverse datasets, applying cutting-edge machine learning at scale to uncover actionable insights—driving data-informed decisions from predictive modeling to strategic execution. We are launching a 12–18 month fully funded faculty fellowship . This is a unique opportunity to pursue advanced machine learning research in a fast-paced, real-world environment—collaborating with teams at the frontier of quantitative trading.

Requirements

• Exceptional faculty (tenured or tenure-track) with expertise in machine learning, deep learning, LLM, statistics, computer science, physics, applied mathematics, or related fields
• Exceptional newly minted PhDs or postdocs developing a research agenda in machine learning, deep learning, LLM, statistics, computer science, physics, applied mathematics, or related fields
• A strong theoretical foundation in ML and a passion for solving practical, open-ended problems
• Strong programming skills (Python preferred); experience with ML frameworks like PyTorch, TensorFlow or Jax
• Intellectual curiosity, adaptability, and a collaborative mindset

Responsibilities

• Conduct applied machine learning research using large-scale, real-world financial datasets
• Develop novel modeling techniques and adapt state-of-the-art algorithms to unique challenges in quantitative finance
• Collaborate with researchers and engineers to translate theoretical insights into production-scale systems.
• Contribute to the design of robust, high-performance ML infrastructure
• Explore research directions aligned with your interests, with flexibility in scope and duration
• Evaluate ideas in an industrial setting, generating insights that may inform future academic or applied work
• Help grow our research community by fostering collaboration and leveraging your network within the ML and academic ecosystems

What This Job Offers

• Education Level: Ph.D. or professional degree
• Number of Employees: 1,001-5,000 employees