Job description

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. ABOUT GOLDMAN SACHS At Goldman Sachs, we commit our people, capital and ideas to help our clients, shareholders and the communities we serve to grow. Founded in 1869, we are a leading global investment banking, securities and investment management firm. Headquartered in New York, we maintain offices around the world. We believe who you are makes you better at what you do. We're committed to fostering and advancing diversity and inclusion in our own workplace and beyond by ensuring every individual within our firm has a number of opportunities to grow professionally and personally, from our training and development opportunities and firmwide networks to benefits, wellness and personal finance offerings and mindfulness programs. Learn more about our culture, benefits, and people at GS.com/careers. We’re committed to finding reasonable accommodations for candidates with special needs or disabilities during our recruiting process. Learn more: goldmansachs.com Salary Range The expected base salary for this New York, NY, United States-based position is $155000-$300000. In addition, you may be eligible for a discretionary bonus if you are an active employee as of fiscal year-end. Benefits Goldman Sachs is committed to providing our people with valuable and competitive benefits and wellness offerings, as it is a core part of providing a strong overall employee experience. A summary of these offerings, which are generally available to active, non-temporary, full-time and part-time US employees who work at least 20 hours per week, can be found here .

Requirements

Must-haves

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.
Collaborate on the strategic development and ongoing expansion of our research infrastructure, quantitative modeling frameworks, and signal analytics engines.
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.

Nice-to-haves

None flagged.

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

machine learningaipythonjava

Platform: goldman-sachs
Effort: medium

Benefits

Benefits detected in the listing.

Wellness