Job Specifications
We are seeking a highly skilled and motivated Quantitative Strategist to join our front-office team. This role is central to building, maintaining, and enhancing models and applications that drive trading, risk management, and portfolio construction across the firm’s global Rates business. You will work directly with portfolio managers, traders, and risk managers to deliver innovative quantitative solutions in a fast-paced, high-impact environment.
Responsibilities
Develop and enhance pricing, risk, and relative value models for rates products, including government bonds, swaps, futures, swaptions, and inflation-linked products.
Build scalable risk platforms and analytics libraries to support intraday and end-of-day trading and risk management.
Collaborate with portfolio managers and traders to design and implement quantitative trading strategies and risk views.
Partner with technology teams to integrate models into production systems, ensuring robust, low-latency, and scalable implementations.
Conduct research and prototyping for curve construction, scenario analysis, VaR, PCA decomposition, and other advanced risk metrics.
Leverage Python, C++, and/or Java for model development, prototyping, and data analysis; use SQL and kdb+/q for large-scale market and trade data handling.
Develop dashboards and visualization tools for portfolio and risk monitoring, ensuring transparency of exposures and P&L attribution.
Support the desk by performing ad hoc analysis, stress tests, and scenario modeling to inform investment and hedging decisions.
Qualifications
Advanced degree (Master’s/PhD) in Quantitative Finance, Mathematics, Computer Science, Physics, Engineering, or a related discipline.
Experience as a Quant, Strat, or Risk Developer in Rates at a top hedge fund, bank, or trading firm.
Deep understanding of fixed income and derivatives products, including yield curve modeling, risk factors, and pricing frameworks.
Strong programming skills in Python and at least one other language (C++ or Java).
Experience with large-scale data platforms (SQL, kdb+/q, or similar).
Ability to communicate complex quantitative concepts clearly to both technical and non-technical stakeholders.
Strong problem-solving mindset, with the ability to work independently and thrive in a fast-paced environment.
Preferred Skills
Familiarity with market data sources (Bloomberg, Refinitiv, etc.) and data APIs.
Experience in building risk platforms or contributing to cross-asset risk infrastructure.
Prior exposure to machine learning methods applied to fixed income or macro trading strategies.
About the Company
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