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Susquehanna International Group
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Machine Learning Researcher – PhD Hire – NY/Philadelphia area Susquehanna International Group, LLP in United States
Degree Level
PhD, Postdoc
Field of study
Computer Science
Funding
Available
Deadline
Apr 13, 2027
Country
United States
University
Susquehanna International Group
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About this position
Susquehanna International Group, LLP is expanding its Quantitative Research machine learning group in the Bala Cynwyd, Pennsylvania area and is seeking a machine learning researcher for research-oriented work at the intersection of advanced ML and systematic trading. The role focuses on forecasting challenges such as time series analysis and natural language understanding, with the goal of improving trading strategies and decision-making through data-driven research.
The position is centered on developing deep learning models for generating and enhancing trading signals across asset classes. The researcher will collaborate with researchers, traders, and developers to improve alpha generation, design rigorous experiments with modern ML frameworks, and turn research findings into production-ready models that can be deployed, monitored, and iterated on in live trading environments.
The team operates within a global quantitative trading firm that emphasizes scientific rigor, curiosity, and innovation. The posting highlights access to high-quality financial datasets and high-performance computing resources, along with a collaborative environment involving researchers, engineers, and traders working on complex market problems.
Funding details
Available
What's required
PhD in computer science, machine learning, mathematics, physics, statistics, or a related field is required. The employer seeks candidates with a strong track record of applying machine learning in academic or industry settings, 5+ years of experience building impactful deep learning systems, and a strong publication record in top-tier conferences such as NeurIPS, ICML, or ICLR. Applicants should have strong programming skills in Python and/or C++, practical experience with ML libraries and frameworks such as PyTorch or TensorFlow in production environments, hands-on experience applying deep learning to time series data, a strong foundation in mathematics, statistics, and algorithm design, excellent problem-solving skills, and the ability to work collaboratively in team-oriented environments.
How to apply
Apply through the AcademicJobsOnline application link. Submit your application materials via the portal and ensure they are complete before the deadline.
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Prepare your application
Review drafts and confirm requirements with the university.
Make your next move.
Prepare your application
Review drafts and confirm requirements with the university.