Role Overview:
We are seeking an experienced Quantitative Developer to design and implement a robust portfolio-level risk and optimization framework. This role focuses on enhancing risk modeling, exposure analysis, and attribution infrastructure to support a systematic equities trading business. The ideal candidate will have deep expertise in quantitative development, modern engineering practices, and experience collaborating closely with quantitative researchers and portfolio managers.
Key Responsibilities:
Develop a proprietary risk and optimization framework leveraging Barra-based models.
Design and maintain infrastructure for risk monitoring, exposure measurement, and performance attribution.
Construct an attribution system to evaluate systematic trading signals.
Build scalable data pipelines for efficient extraction, transformation, and loading (ETL) of data from multiple sources, including Barra, Bloomberg, and other financial data providers.
Requirements & Qualifications:
Experience: Minimum of 5 years in quantitative development within a hedge fund, proprietary trading firm, or investment bank.
Market Knowledge: Strong understanding of equities and futures markets, factor-based models, and execution algorithms.
Technical Expertise:
Advanced proficiency in Python for quantitative analysis and infrastructure development.
Experience with modern engineering methodologies, including data lakes, DevOps, and containerization.
Collaboration: Prior experience working alongside quantitative researchers and portfolio managers to provide technical solutions and support.
