Susquehanna is seeking to enhance trading strategies and decision-making processes through the application of advanced machine learning techniques to forecasting challenges, including time series analysis and natural language understanding.
Requirements
- 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
- 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
Responsibilities
- 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
Other
- PhD in Computer Science, Machine Learning, Mathematics, Physics, Statistics, or a related field
- 5+ years of experience building impactful deep learning systems
- Demonstrated ability to work collaboratively in team-oriented environments
- Excellent problem-solving skills with a creative, research-driven mindset
- Visa sponsorship is available for this position
