Remote Quantitative Rates Researcher - Backtest & Validate

Crossing Hurdles; United States; Remote; AUD 110,000 - 207,000; Full time

Job summary

Crossing Hurdles is seeking a Quantitative Rates Researcher to review AI-generated research and backtest results in fixed income and rates markets. You will assess methodology, bias, and costs, delivering clear written feedback.

This contract role offers remote work in Australia time zones, 10-40 hours per week, with compensation 80–150 AUD per hour and opportunities to influence research soundness and trading implementation.

Qualifications

• Background as a quantitative researcher, analyst, or consultant with fixed income or rates expertise.
• Experience building and backtesting systematic rates strategies at hedge funds, asset managers, or banks.
• Advanced Python (pandas, numpy, scipy) or R for research and data analysis.
• Strong understanding of yield curve modeling and carry/roll-down analytics.
• Ability to evaluate research under real trading conditions including costs and liquidity constraints.

Responsibilities

• Review AI-generated quantitative outputs for fixed income strategies.
• Identify issues like lookahead bias, overfitting, and cost assumptions.
• Evaluate backtesting frameworks for rates-specific mechanics.
• Scrutinize signal construction, factor modeling, and alpha research.
• Provide detailed written feedback on model assumptions and research soundness.
• Collaborate asynchronously with project coordinators to clarify findings.

Skills

Quantitative research

Backtesting

Python

R

Yield curve modeling

Carry/roll-down analytics

Relative value trading

Treasury futures

Job description

Crossing Hurdles is seeking a Quantitative Rates Researcher to review AI-generated research and backtest results in fixed income and rates markets. You will assess methodology, bias, and costs, delivering clear written feedback.

This contract role offers remote work in Australia time zones, 10-40 hours per week, with compensation 80–150 AUD per hour and opportunities to influence research soundness and trading implementation.