Senior Quant Strategist - Derivatives & Alpha

Soros Fund Management LLC; New York (NY); On-site; USD 200,000 - 250,000; Full time

Benefits offered by this job

Year-end discretionary bonus

Job summary

Soros Fund Management LLC seeks an experienced Quantitative Strategist to join as a senior individual contributor, collaborating with portfolio managers, risk, and technology to deliver pricing, alpha generation, and analytics projects. You will own problems from framing through to production, applying practical judgment on what to build or buy.

The role emphasizes independence, a broad remit across asset classes, and a focus on scalable, defensible models in a fast-moving market.

Qualifications

• 7+ years in a quantitative role in financial markets.
• Deep understanding of equity and fixed income derivatives pricing.
• Strong proficiency in Python and SQL; exposure to C++/C# is a plus.

Responsibilities

• Evaluate, select, and maintain derivatives pricing models across the platform.
• Implement pricing models or extensions where existing solutions fall short.
• Assess model limitations and communicate them clearly to stakeholders.
• Work with portfolio managers on alpha research, backtesting, and signal implementation.
• Develop and enhance real-time P&L, risk, and analytics tools for portfolio management teams.
• Prioritize work by business impact and push back where justified by value.
• Communicate complex concepts to technical and non-technical stakeholders.

Skills

Python

SQL

C++

C#

Advanced degree

Education

Advanced degree in Mathematics/Physics/Engineering or similar

Job description

Soros Fund Management LLC seeks an experienced Quantitative Strategist to join as a senior individual contributor, collaborating with portfolio managers, risk, and technology to deliver pricing, alpha generation, and analytics projects. You will own problems from framing through to production, applying practical judgment on what to build or buy.

The role emphasizes independence, a broad remit across asset classes, and a focus on scalable, defensible models in a fast-moving market.