Machine Learning PhD Internship

Job Description

About Susquehanna (SIG)

Susquehanna International Group (SIG) is a quantitative trading firm that operates at the intersection of data, algorithms, and markets. It features a full-time research team, Machine Learning team, researchers, developers, and traders who collaborate to solve high-impact problems. The company leverages vast and diverse datasets, applying cutting-edge machine learning at scale to drive data-informed decisions in predictive modeling and strategic execution. Susquehanna provides an intellectually stimulating and collaborative environment with global reach, offering access to unparalleled financial data and computing resources. It emphasizes rigorous scientific methods to extract signals from complex datasets and shape the understanding of market behavior, with a focus on practical implementation of advanced ML research in quantitative finance and trading. The firm also offers a comprehensive education program with deep dives into its ML, quant, and trading practices.

Job Description: Machine Learning PhD Internship

This is a 10-week immersive internship designed for PhD candidates.

Overview
The Machine Learning PhD Internship offers an opportunity to work on high-impact projects that reflect the challenges and workflows of Susquehanna’s full-time research team. Interns will apply their technical expertise in machine learning and data science to real-world financial problems, gaining a deep understanding of how machine learning integrates into Susquehanna’s research and trading systems. The role involves leveraging extensive and diverse datasets and applying cutting-edge machine learning at scale to drive data-informed decisions in predictive modeling to strategic execution.

What You Can Expect (Responsibilities & Activities)

• Conduct research and develop ML models to identify patterns in noisy, non-stationary data.
• Work side-by-side with the Machine Learning team on real, impactful problems in quantitative trading and finance.
• Bridge the gap between cutting-edge ML research and practical implementation.
• Collaborate with researchers, developers, and traders to improve existing models and explore new algorithmic approaches.
• Design and run experiments using the latest ML tools and frameworks.
• Receive one-on-one mentorship from experienced researchers and technologists.
• Participate in a comprehensive education program with deep dives into Susquehanna’s ML, quant, and trading practices.
• Apply rigorous scientific methods to extract signals from complex datasets and shape understanding of market behavior.
• Explore various aspects of machine learning in quantitative finance from alpha generation and signal processing to model deployment and risk-aware decision making.

What We’re Looking For (Qualifications)

• Education: Currently pursuing a PhD in Computer Science, Machine Learning, Statistics, Physics, Applied Mathematics, or a closely related field.
• Experience: Proven experience applying machine learning techniques in a professional or academic setting.
• Publications: Strong publication record in top-tier conferences such as NeurIPS, ICML, or ICLR.
• Technical Skills: Hands-on experience with machine learning frameworks, including PyTorch and TensorFlow.
• Interests: Deep interest in solving complex problems and a drive to innovate in a fast-paced, competitive environment.

Why Join Us? (Benefits)

• Work with a world-class team of researchers and technologists.
• Access to unparalleled financial data and computing resources.
• Opportunity to make a direct impact on trading performance.
• Collaborative, intellectually stimulating environment with global reach.