Data Analyst | Remote

• Review and assess AI-generated quantitative research and trading strategy outputs focused on fixed income and rates markets.
• Identify and document methodological issues such as lookahead bias, overfitting, and unrealistic transaction cost assumptions.
• Evaluate the accuracy of backtesting frameworks, especially with respect to rates-specific mechanics like carry/roll-down.
• Scrutinize the statistical rigor of signal construction, factor modeling, and alpha research in the provided outputs.
• Deliver detailed written feedback on model assumptions, implementation fidelity, and research soundness.
• Collaborate asynchronously with project coordinators by clarifying findings and suggestions through clear communication.

Requirements

• Background as a quantitative researcher, analyst, or consultant with expertise in fixed income or rates markets.
• Demonstrated experience building and backtesting systematic rates strategies at a hedge fund, asset manager, or bank.
• Advanced proficiency in Python (pandas, numpy, scipy) or R for quantitative research and data analysis.
• Strong understanding of yield curve modeling, carry/roll-down analytics, relative value trading, and Treasury futures.
• Comfort evaluating research under real-world trading conditions, including transaction costs and liquidity constraints.