GBM Public - Systematic Macro Quant Researcher - New York - GBM Public

SRI Conference; New York (NY); On-site; USD 150,000 - 300,000; Full time

Job summary

Goldman Sachs in New York is seeking a FICC Quantitative Researcher at Associate/VP level to join a team transforming fixed income, currencies, and commodities through quantitative trading and automation on the trading floor.

The role focuses on developing market making and pricing tools, applying neural networks, factor models, and scalable calibration frameworks for real-time decision making, collaborating with traders and engineers.

Qualifications

• Excellent academic record in a relevant quantitative field such as physics, mathematics, statistics, engineering, or computer science.
• Strong programming skills in C++, Java, or Python.
• Self-starter with strong self-management skills and ability to manage multiple priorities in a high-pressure environment.

Responsibilities

• Take a leading role on our Quantitative Trading & Market Making desk, building market making and quoting strategies across FICC products.
• 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.
• Implement frameworks to manage risk centrally and build optimal portfolios across FICC asset classes.
• Build model calibration frameworks for our advanced statistical and AI models, operating at scale with large quantities of time series data, ensuring accuracy and compliance.
• Drive our market making strategy development using a range of technologies, and collaborate closely with Quant Developers and core engineering teams to enhance core analytics infrastructure and trading tools.
• Develop and enhance critical pricing, trading, and risk tools, and create new frameworks leveraging trade and franchise data to optimize and systematize market making and hedging strategies.

Skills

C++

Java

Python

Education

Quantitative degree

Job description

FICC Quantitative Researcher, Associate / 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, automating the key decisions taken every day. Our team has a wide remit across product types such as Interest Rates (IR), Foreign Exchange (FX), Credit, and Commodities, with strategies including market making, automatic quoting, central risk books, systematic trading, and algorithmic execution, trading on venues around the world. We deploy statistical analysis techniques and mathematical models, including advanced machine learning and AI, to improve business performance while working closely with traders and salespeople on the trading floor to bring value to our clients and the firm.

Role Responsibilities:

• Take a leading role on our Quantitative Trading & Market Making desk, building market making and quoting strategies across FICC products.
• 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.
• Implement frameworks to manage risk centrally and build optimal portfolios across FICC asset classes.
• Build model calibration frameworks for our advanced statistical and AI models, operating at scale with large quantities of time series data, ensuring accuracy and compliance.
• Drive our market making strategy development using a range of technologies, and collaborate closely with Quant Developers and core engineering teams to enhance core analytics infrastructure and trading tools.
• Develop and enhance critical pricing, trading, and risk tools, and create new frameworks leveraging trade and franchise data to optimize and systematize market making and hedging strategies.

Basic Qualifications:

• Excellent academic record in a relevant quantitative field such as physics, mathematics, statistics, engineering, or computer science.
• Strong programming skills in an object-oriented or functional paradigm such as C++, Java, or Python.
• Self-starter with strong self-management skills, ability to manage multiple priorities and deliver in a high-pressure environment.

Excellent written and verbal communication skills, with the ability to articulate complex quantitative concepts to both technical and non-technical

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: https://www.goldmansachs.com/careers/footer/disability-statement.html

Salary Range

The expected base salary for this New York, New York, United States-based position is $150000-$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.