GBM Public - FICC Quantitative Researcher, Alpha monetization, VP, New York

We are a team of FICC Quantitative Researchers who work to transform the Fixed Income, Currencies, and Commodities (FICC) business through quantitative trading. Our team has a wide remit to trade against the central risk book (CRB), across product types such as Interest Rates (IR), Foreign Exchange (FX), and Commodities. Our trade horizon spans from hours to months. Our data driven alpha generation is based on a variety of mathematical techniques, including advanced machine learning and generative AI models.

Role Responsibilities:

• Take a leading role on our Quantitative Trading desk, bridge the gap between research and the live book. Improve monetization of systematic trading signals
• Translate raw predictive alpha into PnL through optimal position sizing, risk decomposition and dynamic covariance estimation.
• Implement frameworks to manage risk centrally and build optimal portfolios across FICC asset classes to improve risk adjusted returns.
• Use advanced statistical analysis and quantitative techniques - such as neural networks, machine learning, and factor models - to build models that drive systematic alpha strategies which make real-time trading and risk management decisions.
• Collaborate on the strategic development and ongoing expansion of our research infrastructure, quantitative modeling frameworks, and signal analytics engines.

Qualifications:

• 2–10 years of quantitative research experience across the buy-side, including hedge funds, prop shops, and systematic asset managers.
• Proven track record of monetizing alpha signals via portfolio construction, advanced optimization, execution, and risk modeling.
• Thorough knowledge of quantitative investment processes and the underlying factors driving systematic strategy returns.
• Excellent academic record in a relevant quantitative field such as physics, mathematics, statistics, engineering, or computer science.
• Strong programming skills in Python (for research and signal generation) and/or Java (execution systems).
• Self-starter with strong self-management skills, ability to manage multiple priorities and deliver in a fast-paced environment.
• Excellent written and verbal communication skills, with the ability to articulate complex quantitative concepts to both technical and non-technical audiences.