We are seeking a Quantitative Business Analyst to work closely with our portfolio risk research and technology teams to drive the implementation and enhancement of our risk and performance platforms. This role sits at the intersection of finance, technology, and data analysis, requiring a strong mathematical background alongside technical proficiency to translate complex investment models into robust software solutions.

The successful candidate will bridge the gap between portfolio risk management and technical execution, managing the full requirements lifecycle for equity risk modeling and trading tools.

Key Responsibilities

· Serve as the primary liaison between quantitative research and software engineering teams to understand model specifications and translate various investment strategies into clear technical requirements.

· Design and oversee the integration of new quantitative models and datasets into the existing trading and risk infrastructure.

· Perform detailed data analysis and prototyping to validate model inputs/outputs and ensure data integrity across the quantitative research pipeline.

· Develop and maintain comprehensive documentation for quantitative tools and data feeds, including functional specifications, model logic descriptions, and data dictionaries.

· Conduct end-user testing and validation of new features, ensuring that implemented solutions align with the mathematical and business intent of investment professionals and portfolio research teams.

· Conduct deep discovery to understand the nuances of specific asset classes and emerging technologies relevant to fundamental and quantitative investment.

Qualifications

· 2+ years working as a business analyst or project management role within a hedge fund, asset management firm, or investment bank.

· 2+ years of experience with software development lifecycles (SDLC) and Agile methodologies.

· Strong understanding of asset pricing, and quantitative factor risk modelling workflows (e.g., portfolio optimization and construction, fundamentals of risk management).

· Experience working directly with portfolio researchers and software engineers.

· Proficiency in SQL and Python for data analysis and prototyping.

· Excellent written and verbal communication skills, with the ability to convey complex mathematical concepts to technical and non-technical stakeholders.

· Strong problem-solving skills and the ability to translate abstract quantitative challenges into actionable technical specifications.

· Experience or interest in scaling quantitative analytics across portfolio research and enterprise risk platforms.