🌎Quantitative Rates Researcher, Remote- Contract

Xperteez Technology•,
•$80 - $150•Remote

About The Position

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.

Requirements

  • 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

Nice To Haves

  • 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

Responsibilities

  • 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
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