SIG Susquehanna
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 You’ll 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 We’re 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 for this role is $300,000. 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.
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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 We’re 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 for this role is $300,000. 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.
#J-18808-Ljbffr