StreetID · 2 weeks ago
Quantitative Researcher
NYC Metro Area
Full-time
Onsite
Senior LevelStreetID is seeking a highly skilled and motivated Rates Quantitative Strategist to join their 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.
Financial ServicesHuman ResourcesInternetPayments
Hiring Manager
Jesse Marrus
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
Qualification
Required
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
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
Company
StreetID
Financial Career Matchmaking Website
Founded in 2010
11-50 employees
Funding
Current Stage
Early StageLeadership Team
Jesse Marrus
Founder and President
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