PhD ML Researcher: Time-Series & Trading Signals

Trading Interview; Northern (KY); Hybrid; USD 180,000 - 230,000; Full time

Benefits offered by this job

Top-tier data access

High-performance computing resources

Impact on trading performance

Global footprint

Job summary

Susquehanna is expanding its Machine Learning group and seeks exceptional researchers to join as Machine Learning Researchers. You will apply advanced ML techniques to forecasting challenges including time series analysis and natural language understanding, influencing trading strategies and decision-making processes.

You will work at the intersection of cutting-edge research and real-world impact, leveraging top-tier datasets and high-performance computing resources to advance alpha generation

Qualifications

• PhD in computer science, machine learning, mathematics, physics, statistics, or a related field.
• Strong track record applying ML in academic or industry settings with 5+ years 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++.
• Hands-on experience applying deep learning on time series data.

Responsibilities

• 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 ML frameworks to improve predictive signals and trading performance.
• Apply scientific methods to extract actionable signals from complex datasets, deepening market understanding.

Skills

Deep learning

Time series

PyTorch

Python

Team collaboration

Education

PhD in CS/ML/Math/Physics

Tools

PyTorch

TensorFlow

Job description

Susquehanna is expanding its Machine Learning group and seeks exceptional researchers to join as Machine Learning Researchers. You will apply advanced ML techniques to forecasting challenges including time series analysis and natural language understanding, influencing trading strategies and decision-making processes.

You will work at the intersection of cutting-edge research and real-world impact, leveraging top-tier datasets and high-performance computing resources to advance alpha generation