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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