Data Analyst | Remote

Crossing Hurdles; South Africa; Remote; ZAR 1,823,000 - 3,419,000; Full time

Job summary

Crossing Hurdles is seeking a Quantitative Rates Researcher to review AI-generated quantitative research and trading strategy outputs focused on fixed income and rates markets. The role emphasizes identifying lookahead bias, overfitting, and unrealistic cost assumptions.

You will backtest frameworks, assess carry/roll-down mechanics, and evaluate signal construction and alpha research. Collaboration is asynchronous with project coordinators, providing detailed written feedback on model

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, and Treasury futures.
• Comfort evaluating research under real-world trading conditions, including transaction costs and liquidity constraints.

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, 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.

Skills

Fixed income expertise

Quant research background

Backtesting experience

Tools

Python

R

Job description

• 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.

Position:

Quantitative Rates Researcher

Type:

Contract

Compensation:

$80 - $150/hour

Location:

Remote

Commitment:

10-40 hrs/week

Role 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, 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.