ML Researcher: Trading AI & Time Series

Trading Interview; Northern (KY); Hybrid; USD 150,000 - 230,000; Full time

Job summary

Susquehanna is expanding its Machine Learning group and seeking exceptional researchers to join our team 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.

The ideal candidate has a PhD and a proven track record with deep learning systems, strong programming skills, and a passion for production-ready research in a fast-paced

Qualifications

• PhD in computer science, ML, mathematics, physics, statistics, or related field.
• 5+ years of experience building impactful deep learning systems.
• Strong publication record in NeurIPS, ICML, or ICLR.
• Strong programming skills in Python and/or C++.
• Practical knowledge of ML libraries, PyTorch or TensorFlow, in production environments.
• Hands-on experience applying deep learning on time series data.

Responsibilities

• Conduct research and develop ML models to enhance trading strategies with focus on deep learning.
• Collaborate with researchers, developers, and traders to improve models.
• Design and run experiments using the latest ML tools and frameworks.
• Develop automation tools to streamline research and system development.
• Apply scientific methods to extract signals from complex datasets.
• Partner with engineering teams to test models in production environments.

Skills

Deep learning

Time-series forecasting

Python

C++

Research mindset

Collaboration

Experiment design

Education

PhD in computer science or related field

Tools

PyTorch

TensorFlow

Job description

Susquehanna is expanding its Machine Learning group and seeking exceptional researchers to join our team 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.

The ideal candidate has a PhD and a proven track record with deep learning systems, strong programming skills, and a passion for production-ready research in a fast-paced