Machine Learning PhD Internship

Job Description

About the Company

Susquehanna (SIG) is a firm deeply involved in quantitative trading and finance, leveraging machine learning into its research and trading systems. It is characterized by its world-class team of researchers and technologists, offering unparalleled financial data and computing resources. The company fosters a collaborative, intellectually stimulating environment with global reach, where interns and full-time staff work on high-impact problems at the intersection of data, algorithms, and markets. Susquehanna aims to drive data-informed decisions in predictive modeling and strategic execution, shaping the understanding of market behavior.

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Job Description: Machine Learning PhD Internship

Overview

The Machine Learning PhD Internship at Susquehanna is a 10-week immersive experience tailored for PhD candidates. This internship is designed for individuals passionate about solving high-impact problems at the intersection of data, algorithms, and markets. Interns will work on projects that closely mirror the challenges and workflows of Susquehanna’s full-time research team, applying their technical expertise in machine learning and data science to real-world financial problems. A key aspect of the role is developing a deep understanding of how machine learning integrates into Susquehanna’s research and trading systems, leveraging vast and diverse datasets and applying cutting-edge machine learning at scale to drive data-informed decisions in predictive modeling and strategic execution.

What You Can Expect (Key Responsibilities & Learning Opportunities)

• Conduct research and develop ML models to identify patterns in noisy, non-stationary data.
• Work side-by-side with our Machine Learning team on real, impactful problems in quantitative trading and finance, bridging 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 our 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.
• Strong publication record in top-tier conferences such as NeurIPS, ICML, or ICLR.
• Hands-on experience with machine learning frameworks, including PyTorch and TensorFlow.
• Attributes: Deep interest in solving complex problems and a drive to innovate in a fast-paced, competitive environment.

Why Join Us? (Benefits & Work Environment)

• 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.