Advanced ML Researcher: Forecasting & Trading Signals

Susquehanna International Group; Bala Cynwyd (PA); On-site; USD 150,000 - 230,000; Full time

Benefits offered by this job

World-class team

Best-in-class data

High-performance computing

Job summary

Susquehanna International Group in the United States is seeking a Machine Learning Researcher to apply advanced ML to forecasting challenges, including time series analysis and NLP, with direct impact on trading strategies.

You will translate research insights into production-ready models and collaborate with researchers, traders, and developers to deploy, monitor, and iterate on models in live trading environments.

Qualifications

• PhD in CS/ML/related field.
• 5+ years of deep learning experience.
• Top-tier publications in NeurIPS/ICML/ICLR.
• Strong Python and/or C++ programming.
• Experience with PyTorch or TensorFlow in production.
• Hands-on time-series deep learning.
• Solid mathematics and statistics foundation.
• Collaborative, research-driven mindset.

Responsibilities

• Research and develop deep learning models for systematic trading signals across asset classes.
• Collaborate with researchers, traders, and developers to improve alpha generation.
• Design and conduct rigorous experiments using modern ML frameworks to improve predictive signals.
• Apply scientific methods to extract actionable signals from complex datasets.
• Translate research insights into production-ready models for live trading environments.
• Partner with engineering and trading teams to deploy and monitor models.

Skills

Python

C++

Deep learning

Time series

Research

Collaboration

Education

PhD in computer science or related field

Tools

PyTorch

TensorFlow

Job description

Susquehanna International Group in the United States is seeking a Machine Learning Researcher to apply advanced ML to forecasting challenges, including time series analysis and NLP, with direct impact on trading strategies.

You will translate research insights into production-ready models and collaborate with researchers, traders, and developers to deploy, monitor, and iterate on models in live trading environments.