As a Machine Learning Researcher, you will apply advanced ML techniques to a wide range of forecasting challenges, including time series analysis, natural language understanding, and more. Your work will directly influence our trading strategies and decision-making processes. This is a unique opportunity to work at the intersection of cutting-edge research and real-world impact, leveraging one of the highest-quality financial datasets in the industry.

We’re looking for research scientists with a proven track record of applying deep learning to solve complex, high-impact problems. The ideal candidate will have a strong grasp of diverse machine learning techniques and a passion for experimenting with model architectures, feature engineering, and hyperparameter tuning to produce resilient and high-performing models.

What you'll do

• Research and develop deep learning models to generate and enhance systematic trading signals and strategies across asset classes.
• Collaborate closely with researchers, traders, and developers to improve alpha generation and identify new algorithmic trading strategies.
• Design and conduct rigorous experiments using modern machine learning frameworks to improve predictive signals and overall trading performance.
• Apply scientific methods to extract actionable signals from complex datasets, deepening the understanding of market behavior.
• Translate research insights into production-ready models that can be implemented, tested, and validated in live trading environments.
• Partner with engineering and trading teams to deploy, monitor, and iterate on models that drive trading decisions and execution outcomes.

• PhD in computer science, machine learning, mathematics, physics, statistics, or a related field
• Strong track record of applying ML 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, especially in production environments
• Hands-on experience applying deep learning on time series data
• Strong foundation in mathematics, statistics, and algorithm design
• Excellent problem-solving skills with a creative, research-driven mindset
• Demonstrated ability to work collaboratively in team-oriented environments
• A passion for solving complex problems and a drive to innovate in a fast-paced, competitive environment
• Visa sponsorship is available for this position

The annual base pay for this role is $300,000. Susquehanna considers factors such as scope and responsibilities of the position, work experience, education/training, key skills, as well as market and organizational considerations when extending an offer.

What we offer

• Collaborate with a world-class team of researchers, engineers, and traders
• Gain access to best-in-class financial data and high-performance computing resources
• Directly impact real-time trading performance through your work
• Thrive in a collaborative, intellectually rigorous environment with a global footprint

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