About DSG
The Data Strategies Group (DSG) is a central quantitative research team that works alongside investment teams at the forefront of alternative data, AI/ML research, and quantitative modeling. As a Quantitative Researcher in DSG, you will build advanced models to infer how the real world evolves from noisy and complex data sources and work with investment teams to apply our insights to critical investment problems across Citadel’s investment strategies.
Key Responsibilities
- Innovation: Stay at the frontier of quantitative and AI/ML methods, applying cutting-edge academic and industry research to maximize utilization of large-scale data for real-world investment opportunities.
- Model Development: Build analysis tools and statistical models around petabyte scale alternative datasets ranging from high frequency sensor data to unstructured event data gathered from the real world to predict economic events across all sectors and asset classes.
- Signal Research: Partner with investment teams to test hypotheses, validate signals, and integrate findings into systematic and discretionary strategies.
- Discovery & Evaluation: Identify, assess, and enhance alternative datasets for quality, coverage, and potential investment relevance.
- Entrepreneurship: Act as an intellectual entrepreneur and owner by identifying new data sources, researching answers to novel questions, and developing innovative approaches that have the potential to create commercial impact.
What we offer
- The opportunity to work at the forefront of quantitative finance with access to the world’s most comprehensive and exclusive alternative data and world-class computing infrastructure.
- A culture of learning among the most talented and accomplished investment professionals, researchers, and developers in the world. Our colleagues are empowered to test their ideas and develop solutions that accelerate their growth and drive real impact.
Required Skills
Technical & analytical skills:
- Degree (Ph.D., Master’s, or Bachelor’s) in a quantitative discipline such as Statistics, Mathematics, Computer Science, Physics, Neuroscience, Engineering, Economics, or Operations.
- Advanced expertise in statistical inference, machine learning, and data science, with practical experience in high-dimensional datasets.
- Exceptional command of programming languages such as Python, C++, R, or Julia; ability to write production-quality research code.
- Demonstrated ability to design experiments, test hypotheses, and interpret results rigorously and independently.
Soft skills:
- Strong verbal and written communication skills, with the ability to explain technical results to non-technical stakeholders.
- Quantitative intuition and creativity with a passion for uncovering insights in complex datasets.
Intrinsics:
- Intellectual curiosity and willingness to learn about financial markets, asset classes, investment strategies, and alternative data.
- Self-starter with strong proactivity, ownership, and willingness to drive commercial impact.
- Thrives in a fast-paced, collaborative, and results-oriented environment.
