Machine Learning Internship - PhD: 2027 at Susquehanna… · Bala…

Summary: Susquehanna International Group is a global quantitative trading firm that emphasizes scientific rigor and innovation. They are seeking a Machine Learning Intern for a 10-week immersive experience, where candidates will work on impactful projects applying machine learning to financial problems while collaborating with a team of researchers and technologists. Responsibilities: - 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 Required Qualifications: - 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 Required Skills: Machine Learning, Data Science, Quantitative Trading, Financial Modeling, Research, Machine Learning Frameworks, PyTorch, TensorFlow, Scientific Methods, Signal Processing, Model Deployment, Risk-aware Decision Making, Drive to innovate Graduation Date Requirement: Graduate in 2027