Data Analyst | Remote

Crossing Hurdles; La Réunion; Remoto; EUR 99.000 - 185.000; Part-time

Descrizione del lavoro

Crossing Hurdles is seeking a Quantitative Rates Researcher for remote collaboration. You will review AI-generated quantitative research and trading strategy outputs focused on fixed income and rates markets, identify methodological issues, and evaluate backtesting frameworks.

The role offers 10-40 hrs/week under a contract arrangement. Applicants should have a background as a quantitative researcher or analyst with fixed income expertise, plus experience building and backtesting systematic

Competenze

• Background as a quantitative researcher, analyst, or consultant with fixed income or rates expertise.
• Experience building and backtesting systematic rates strategies for hedge funds or banks.
• Strong Python (pandas, numpy, scipy) or R for data analysis.
• Understanding of yield curve modeling and carry/roll-down analytics.
• Knowledge of Treasury futures and liquidity constraints in trading.

Mansioni

• 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.

Conoscenze

Python

R

Pandas

Numpy

Scipy

Fixed income

Rates markets

Strumenti

Backtesting frameworks

Descrizione del lavoro

• 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.