Quantitative Rates Researcher, Remote- Contract

Role Title: Quantitative Rates Researcher Role Type: Contract Location: Remote Required Skills: Python R Pandas Numpy Scipy Fixed income analysis Rates markets expertise Systematic strategy backtesting Yield curve modeling Carry/roll-down analytics Relative value trading Sofr/eurodollar instruments Treasury futures Statistical rigor Factor modeling Alpha research Transaction cost analysis Liquidity assessment Model validation Written communication Attention to detail Quantitative research Data analysis Reviewing methodological issues (lookahead bias, overfitting, data snooping) Collaborative communication In this role, you'll apply your expertise to help train next-generation AI systems. Your work will shape how models learn, reason, and perform through high-quality, real-world input. No prior experience in AI is required - your domain knowledge is what matters. Scope of Work: 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, data snooping, and unrealistic transaction cost assumptions Evaluate the accuracy of backtesting frameworks, especially with respect to rates-specific mechanics like carry/roll-down and contract roll conventions 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 written and verbal communication Contribute to the refinement of research evaluation processes for greater accuracy and relevance Preferred Qualifications: 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, SOFR/Eurodollar instruments, and Treasury futures Comfort evaluating research under real-world trading conditions, including transaction costs and liquidity constraints Exceptional attention to detail and ability to articulate complex quantitative findings in clear, concise written feedback Prior experience assessing or reviewing models for compliance with best practices in quantitative finance is a plus Originally posted on Himalayas