Treasury Quantitative Researcher
A top-tier hedge fund is expanding their Treasury Quant team and is seeking to speak with Quantitative Researchers to drive capital efficiency across global portfolios. The firm is placing an increasing emphasis on capital efficiency and liquidity strategy, as they expand with multiple new roles to build out advanced analytics and optimization capabilities. This is a high-impact, front-office aligned opportunity at the intersection of quantitative modeling, liquidity strategy, and margin optimization.
You'll be building the models that power the firm's capital deployment decisions - from designing risk-based margin allocation frameworks to optimizing cross-asset liquidity buffers. Your work will directly influence how billions are allocated across equities, fixed income, credit, and commodities.
What You'll Do:
- Architect and implement cutting-edge margin optimization models across asset classes.
- Build Python-based analytics libraries for capital utilization and margin attribution.
- Collaborate with PMs, Risk, and Treasury to refine firm-wide portfolio construction.
- Expand the quantitative framework for managing liquidity, cash, and collateral.
- Own real-world optimization problems using optimization engines.
What You Bring:
- 5+ years in quantitative research within hedge funds, banks, or asset managers.
- A PhD or MS in a quantitative field (Math, Statistics, Physics, Computer Science).
- Deep modeling expertise and hands-on Python skills (numpy, scipy, pandas).
- Real-world experience solving complex optimization problems.
- Strong product knowledge across multiple asset classes.
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