Machine Learning Researcher - PhD: 2026 Job at Susquehanna International Group, New York, NY

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  • Susquehanna International Group
  • New York, NY

Job Description

Overview

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

Overview

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

What Youll Do

  • Conduct research and develop ML models to enhance trading strategies, with a focus on deep learning and scalable deployment
  • Collaborate with researchers, developers, and traders to improve existing models and explore new algorithmic approaches
  • Design and run experiments using the latest ML tools and frameworks
  • Develop automation tools to streamline research and system development
  • Apply rigorous scientific methods to extract signals from complex datasets and shape our understanding of market behavior
  • Partner with engineering teams to implement and test models in production environments

What We're Looking For

Were 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.

  • 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

Why Join Us?

  • 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

Recruiting for this position will begin in July.

The annual base pay range for this role is $300,000 + discretionary bonus + benefits. 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.

Visa sponsorship is available for this position.

If you're a recruiting agency and want to partner with us, please reach out to recruiting@sig.com . Any resume or referral submitted in the absence of a signed agreement will not be eligible for an agency fee.
Seniority level
  • Seniority level
    Mid-Senior level
Employment type
  • Employment type
    Full-time
Job function
  • Job function
    Other

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