Soros Fund Management LLC (SFM) is seeking a Quantitative Research Analyst to partner with portfolio managers and researchers to generate insights that drive investment strategies by leveraging advanced AI, data science methods, and machine learning to analyze complex datasets, develop predictive signals, and evaluate market dynamics.
Requirements
- Strong proficiency in Python and modern data science libraries (Pandas, NumPy, Scikit-learn, PyTorch, TensorFlow, etc.).
- Demonstrated expertise in machine learning, NLP, and quantitative research methods.
- Experience designing and testing predictive models with large financial datasets.
- Familiarity with model governance practices.
Responsibilities
- Partner with our portfolio managers and analysts to solve problems where AI and quant technology can enhance research, operations, and decision making.
- Deliver production-grade AI tools focused on analysis, such as tonal analysis of earnings calls or summarization of Bloomberg IB chat.
- Conduct data-driven research across diverse asset classes to uncover patterns, relationships, and predictive signals.
- Quantitative support for desk projects such as reporting, back testing, development and implementation of new models
- Be the primary liaison between technology and our fundamental portfolio managers in delivering the above
- Document research methods, results, and best practices for use across the investment
Other
- Bachelor’s Degree in a STEM field. Advanced degree preferred.
- 5+ years of relevant work experience in a front office quantitative role.
- Excellent communication skills targeting technical and non-technical audiences.
- Smart risk-taking
- Owner’s Mindset
