Job Description

Millennium's Global Risk Management Department is responsible for identifying, measuring, monitoring, managing, and reporting on the risks associated with Millennium portfolios. Our Risk Management organization is designed to accommodate the overall size, nature, and complexity of the firm's trading activities. We are looking to add an inquisitive minded

Risk Modeler to

join our team. You will have the opportunity to develop and maintain the quantitative frameworks used by our portfolio managers and senior management teams. You will be responsible for the framework which involves

Cash Equities Factor modelling, Statistical Factor modeling, tail risk (e.g. VaR, Stress) modeling, performance analytics (e.g. Drawdowns, Sharpe), and developing optimization toolkits. If you're passionate about quantitative finance, portfolio management, and applied statistics, we'd love to hear from you.

Your primary responsibilities will encompass:

Factor Model and Risk Measurement:

Develop and maintain robust frameworks for factor modeling and risk measurements. Strong emphasis on using these models for portfolio optimization and risk and attribution analysis.

Quantitative Framework Development:

Assist in the creation and optimization of our quantitative framework, which includes collaborating with technology, risk, portfolio, and business managers.

Tech Collaboration:

Partner with the Technology department to streamline the transition of quantitative models into production environments. The priority is to ensure accuracy and efficiency in day-to-day workflows.

Research Model Development:

Lead research into and implementation of various quantitative models, including but not confined to factor models and complex risk assessments.

Qualifications/Skills

Required:

The candidate should have a degree in a quantitative major: statistics, mathematics, engineering, and either professional experience of 1-4 years in a quantitative role in a financial organization, or an advanced degree in a quantitative field preferred. Strong programming skills, prior experience with Python (Polars and/or Pandas) or SQL. Proficiency in at least a compiled and statically typed language is a plus; so is demonstrated programming ability on public repositories e.g., GitHub. Prior experience in Equity Factor Risk modeling, quantitative models and portfolio analytics. Experience using fundamental equity factor models like MSCI/Barra, Axioma or Bloomberg is highly desirable. * Sense of responsibility and integrity. Intellectual curiosity and spirit of initiative. Ability to work independently and effectively manage ambiguity.