Quant Risk Researcher

Millennium•New York, NY

3d•$160,000 - $250,000

About The Position

Millennium's Global Risk Management Department identifies, measures, monitors, manages and reports portfolio risks at both the firm-wide and Portfolio Manager levels, with a focus on market, credit and liquidity risks. The team establishes and monitors trading parameters, risk guidelines and performance metrics across regions and product classes, and aggregates risk at the firm-wide level. Within Risk Management, this role partners directly with Portfolio Managers running systematic and quantitative strategies across global futures, FX, rates, equity index and commodities. The team combines risk management with quantitative research and performance analytics to understand, represent and monitor how strategies behave. The Quant Risk Researcher will monitor and explain P&L, performance and risk; build quantitative models and analytics; research risk methodologies; develop simulation and pricing models; and improve research and analytics infrastructure. The role will also apply machine learning and AI techniques and work closely with Portfolio Managers, risk managers and technologists to bring research into production.

Requirements

Master's degree or PhD in a quantitative field such as mathematics, engineering, computer science or physics.
Experience in a trading, risk or quantitative research role, such as alpha research, portfolio optimization or risk modeling, within a hedge fund, asset manager or similar trading environment.
Strong coding skills, including Python (pandas, NumPy, SciPy, scikit-learn or similar), SQL, kdb+/q and C++.
Excellent command of statistics, time series analysis and optimization methods, with rigorous model evaluation and skepticism about overfitting.
Strong analytical, problem-solving and attention-to-detail skills, with intellectual curiosity about markets.
Ability to work independently, own projects end to end and prioritize in a fast-moving, high-pressure, changing environment.
Strong teamwork, written and verbal communication skills, and ability to build working relationships with Portfolio Managers and across the Risk team.

Nice To Haves

PhD in a quantitative field.
Experience in volatility, rates or quantitative macro strategies.
Experience applying machine learning or AI techniques.
Experience in GUI development.
An applied, practical mindset and preference for solving real problems.

Responsibilities

Monitor and explain P&L, performance and risk for Quantitative Strategies Portfolio Managers across global futures, FX, rates, equity index and commodities, engaging with them regularly.
Build quantitative models and analytics for performance attribution and risk analysis using large and diverse datasets.
Research and implement risk methodologies and techniques to represent and monitor systematic strategies, considering robustness, implementation and liquidity.
Develop and refine simulation models for risk measurement, including VaR enhancements, scenario analysis and factor modeling.
Design and enhance pricing models and visualization tools to make risk and performance transparent to Portfolio Managers and the broader Risk team.
Improve research and analytics infrastructure, including data pipelines, backtesting tools and performance analytics.
Apply machine learning and AI techniques to strengthen risk and performance analytics.
Partner with Portfolio Managers, risk managers and technologists to move ideas from research into production.