Deep Learning Researcher for Quantitative Trading

SIG Susquehanna; Pennsylvania; On-site; USD 150,000 - 230,000; Full time

Job summary

SIG Susquehanna seeks a Machine Learning Researcher to apply advanced ML techniques to forecasting challenges across asset classes. You will develop deep learning models to generate and enhance trading signals, collaborating with researchers, traders, and developers to improve alpha generation and production deployment.

The ideal candidate has a PhD with 5+ years of experience building impactful DL systems, strong publication record, and hands-on expertise with PyTorch/TensorFlow in production.

Qualifications

• PhD in a related field with strong ML background.
• 5+ years of experience building impactful DL systems in academia or industry.
• Prolific publication record in venues like NeurIPS/ICML/ICLR.
• Strong Python and/or C++ programming skills.
• Hands-on ML with PyTorch or TensorFlow in production environments.
• Experience applying DL to time series data and trading signals.

Responsibilities

• Research and develop deep learning models to generate and enhance trading signals.
• Collaborate with researchers, traders, and developers to improve alpha generation.
• Design rigorous experiments using modern ML frameworks to boost predictive signals.
• Extract actionable insights from complex market datasets.
• Translate research insights into production-ready models for live trading.
• Partner with engineering and trading teams to deploy and monitor models.

Skills

PhD in related field

5+ years of DL systems

Python/C++ programming

PyTorch/TensorFlow in production

Time series ML experience

Education

PhD in computer science/ML/related field

Tools

PyTorch

TensorFlow

Time series libraries

Job description

SIG Susquehanna seeks a Machine Learning Researcher to apply advanced ML techniques to forecasting challenges across asset classes. You will develop deep learning models to generate and enhance trading signals, collaborating with researchers, traders, and developers to improve alpha generation and production deployment.

The ideal candidate has a PhD with 5+ years of experience building impactful DL systems, strong publication record, and hands-on expertise with PyTorch/TensorFlow in production.