Susquehanna International Group
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Machine Learning Researcher – PhD Hire – NY/Philadelphia area Susquehanna International Group in United States
Degree Level
PhD
Field of study
Computer Science
Funding
Available
Deadline
Apr 14, 2027
Country
United States
University
Susquehanna International Group
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About this position
Susquehanna International Group is expanding its Machine Learning group within Quantitative Research in Bala Cynwyd, Pennsylvania, and is seeking a Machine Learning Researcher to join its team. The role sits in a global quantitative trading environment where machine learning and advanced quantitative research are used to uncover signals from large financial datasets and support systematic trading strategies.
The researcher will work on forecasting problems spanning time series analysis, natural language understanding, and related machine learning challenges. The position focuses on developing deep learning models that can improve trading signals and strategies across asset classes, with an emphasis on scientific experimentation and translating research outcomes into production-ready models for live trading environments.
The role is embedded in a collaborative environment that brings together researchers, traders, engineers, and developers. The posting highlights access to high-quality financial data and high-performance computing resources, along with the opportunity to influence real-time trading performance through research that is directly connected to market behavior and algorithmic strategy development.
This is a research-intensive industry opening for candidates who want to apply modern machine learning methods to high-impact quantitative problems in a fast-paced trading setting.
Funding details
Available
What's required
PhD in computer science, machine learning, mathematics, physics, statistics, or a related field is required. Applicants should have a strong track record of applying machine learning in academic or industry settings, with 5+ years of experience building impactful deep learning systems, a strong publication record in top-tier conferences such as NeurIPS, ICML, or ICLR, strong programming skills in Python and/or C++, practical knowledge of ML libraries and frameworks such as PyTorch or TensorFlow, hands-on experience applying deep learning to time series data, a strong foundation in mathematics, statistics, and algorithm design, excellent problem-solving skills, demonstrated ability to work collaboratively, and a passion for solving complex problems in a fast-paced competitive environment.
How to apply
Apply through the MathJobs posting at the application link provided. Submit the requested application materials through the portal by 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.