Our Machine Learning PhD Internship is a 10-week immersive experience designed for PhD candidates who are passionate about solving high-impact problems at the intersection of data, algorithms, and markets.
As a Machine Learning Intern at Susquehanna, you’ll work on high-impact projects that closely reflect the challenges and workflows of our full-time research team. You’ll apply your technical expertise in machine learning and data science to real-world financial problems, while developing a deep understanding of how machine learning integrates into Susquehanna’s research and trading systems. You will leverage vast and diverse datasets and apply cutting-edge machine learning at scale to drive data-informed decisions in predictive modeling to strategic execution.
What You Can Expect
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
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
Currently pursuing a PhD in Computer Science, Machine Learning, Statistics, Physics, Applied Mathematics, or a closely related field
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
Deep interest in solving complex problems and a drive to innovate in a fast-paced, competitive environment
Why Join Us?
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
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Machine Learning