Cross Asset Risk Research

Millennium • New York, NY

4d • $175,000 - $250,000

About The Position

The firm is looking for a quantitative researcher to join a new Cross Asset Risk team. The goal of the team is to build a unified set of risk data for decision-makers at the firm level to make informed decisions about Millennium’s complex set of positions. The team will be coordinating with multiple different asset-class risk teams to build the firm’s high-level view, including building out individual asset-class risk analytics in cases where it is deemed necessary. This role involves research into using many different statistical and probabilistic techniques to evolve the firm’s understanding of risk. Key to the role will be understanding the ways in which different market structures impact their individual asset classes, the behavior of large market participants, shared traits of popular trading strategies, and developing probabilistic methodologies to anticipate potential stress scenarios.

Requirements

• 1–5 years of hands-on experience in quantitative research, modeling, or applied ML
• Strong foundation in applied mathematics / statistics / machine learning (especially probability theory, linear algebra, calculus, and statistics)
• Demonstrated ability to design, implement, and validate models from scratch (not just apply off-the-shelf packages)
• Python proficiency for research prototyping and analysis
• Experience with deep learning frameworks (For example, PyTorch/TensorFlow)
• Strong research habits: hypothesis formation, experimentation, back testing/validation, and clear communication

Nice To Haves

• Financial markets experience is helpful but not required

Responsibilities

• Build and validate cross-asset risk measures.
• Identify market factors across asset classes and identify common risk premia trades.
• Apply feature discovery and classification-style ML to identify and interpret portfolio/trade drivers with careful validation and robustness testing.
• Partner closely with asset class risk teams to test assumptions, interpret results, and drive adoption of the analytics.
• Develop forward-looking scenario models, identifying risks in the firm shared across asset classes.

What This Job Offers

• Job Type: Full-time
• Career Level: Entry Level
• Education Level: No Education Listed