Quantitative Business Analyst - Equity Factor Models

Millennium•New York, NY

12d•$175,000 - $250,000

About The Position

Millennium is seeking a Quantitative Business Analyst for its Equity Factor Model team. The team partners across portfolio risk research, equity risk modeling, and technology to advance risk and performance platforms that support quantitative research and investment decision-making. The role serves as the link between quantitative research and software engineering, managing requirements and delivery for equity risk modeling and trading tools, integrating models and datasets into trading and risk infrastructure, validating data and model outputs, and documenting tools and data feeds.

Requirements

Advanced degree (PhD or Master’s) in finance, financial engineering, mathematics, statistics, economics, physics, computer science, or another quantitative discipline.
At least 2 years of professional work experience (post-PhD) as a business analyst or project manager within a hedge fund, asset management firm, or investment bank; 5+ years for Master’s degree holders.
At least 2 years of professional work experience with software development lifecycles and Agile delivery methodologies; 5+ years for Master’s degree holders.
Strong knowledge of asset pricing, quantitative factor risk modeling, portfolio optimization and construction, and core risk management concepts.
Proficiency in Python and SQL for data analysis, validation, and prototyping.
Experience partnering directly with portfolio researchers and software engineers to translate complex quantitative needs into actionable technical specifications.
Excellent written and verbal communication skills, including the ability to explain mathematical concepts accurately to technical and non-technical stakeholders.

Nice To Haves

CFA designation.
Experience with equity factor risk models, performance measurement and attribution, data quality controls, reproducible pipelines, model governance, or market data technologies.

Responsibilities

Serve as the primary liaison between quantitative research and software engineering, translating model specifications and investment strategies into clear, testable technical requirements.
Manage the end-to-end requirements lifecycle for equity risk modeling and trading tools, from discovery and functional specifications through acceptance criteria and delivery.
Design and oversee the integration of quantitative models and datasets into the firm’s trading and risk infrastructure.
Analyze and prototype against market, portfolio, and model data to validate inputs and outputs, strengthen data integrity, and support the quantitative research pipeline.
Lead end-user testing and feature validation to ensure delivered solutions reflect the mathematical and business intent of investment professionals and portfolio research teams.
Create and maintain documentation for quantitative tools and data feeds, including functional specifications, model logic descriptions, and data dictionaries.