Systematic Quantitative Researcher - Fixed Income (Rates & Credit)
A leading quantitative trading and market-making firm is seeking a Systematic Quantitative Researcher to join a growing Fixed Income research team focused on developing and scaling alpha-driven trading strategies across global Rates and Credit markets. This is a highly impactful role working at the intersection of alpha research, systematic portfolio construction, and execution optimization.
The team is actively expanding its systematic Fixed Income platform and is interested in researchers with experience in rates, credit, rates volatility, or broader FICC products. Researchers focused on either signal generation or monetization/execution research are encouraged to apply.
Responsibilities

• Research, develop, and implement systematic alpha signals across global fixed income markets, with a focus on Rates and Credit products.
• Identify predictive features from large and diverse datasets, including market microstructure, order flow, macroeconomic, positioning, and alternative data sources.
• Design and test intraday, short-term, and medium-horizon trading signals ranging from minutes to several days.
• Develop portfolio construction and risk allocation frameworks to improve signal monetization and strategy performance.
• Partner closely with trading, technology, and execution teams to deploy research into production environments.
• Analyze market behavior around macro events, liquidity regimes, and cross-asset relationships to uncover new sources of alpha.
• Improve research infrastructure, backtesting frameworks, and data pipelines to accelerate strategy development.

Qualifications

• Advanced degree (MS or PhD preferred) in Mathematics, Statistics, Physics, Computer Science, Engineering, Economics, or a related quantitative discipline.
• Strong background in systematic trading, quantitative research, or alpha generation within Rates, Credit, Rates Volatility, or broader FICC markets.
• Demonstrated experience developing predictive signals with holding periods ranging from intraday to multi-day.
• Strong understanding of fixed income market structure, relative value relationships, yield curve dynamics, or credit market behavior.
• Expertise in statistical modeling, machine learning, time-series analysis, and large-scale data analysis.
• Strong programming skills in Python. Experience with C++, Java, or other performance-oriented languages is a plus.
• Ability to independently conduct research and communicate findings to both technical and trading audiences.

Preferred Backgrounds
We are particularly interested in candidates with experience in one or more of the following areas:

• Alpha signal generation in Rates, Credit, Rates Options, Futures, Swaps, or related fixed income products.
• Systematic macro or cross-asset research.
• Execution, market microstructure, or signal monetization research.
• Statistical arbitrage and short-term predictive modeling.
• Machine learning applications within systematic trading.
• Portfolio construction and risk modeling for systematic fixed income strategies.
• Intraday through multi-day forecasting models.