Remote Quantitative Rates Researcher

Remotebridge; United States; Remote; USD 96,000 - 179,000; Full time

Job summary

Remotebridge is seeking a Quantitative Rates Researcher for a remote contractor role. You will review AI-generated research and trading outputs related to fixed income and rates, identifying biases and backtesting issues while documenting findings for senior researchers.

The position requires strong Python or R skills and experience with rate-market analytics, carry/roll-down concepts, and yield curve modeling. You will communicate clearly in written feedback and help refine evaluation processes.

Qualifications

• Background as a quantitative researcher or analyst in fixed income or rates markets.
• Experience backtesting systematic rates strategies is highly desired.
• Strong Python or R skills for quantitative research and data analysis.

Responsibilities

• Review AI-generated quantitative research and trading outputs focused on fixed income and rates markets.
• Identify methodological issues (lookahead bias, overfitting, data snooping, costs).
• Evaluate backtesting frameworks for rates-specific mechanics (carry/roll-down, roll conventions).
• Assess statistical rigor of signal construction, factor modeling, and alpha research.
• Deliver written feedback on model assumptions and research soundness.
• Collaborate asynchronously with project coordinators via clear written communication.
• Refine research evaluation processes for improved accuracy.

Skills

Python

Pandas

NumPy

SciPy

R

Tools

Python IDE

Jupyter

Job description

Remotebridge is seeking a Quantitative Rates Researcher for a remote contractor role. You will review AI-generated research and trading outputs related to fixed income and rates, identifying biases and backtesting issues while documenting findings for senior researchers.

The position requires strong Python or R skills and experience with rate-market analytics, carry/roll-down concepts, and yield curve modeling. You will communicate clearly in written feedback and help refine evaluation processes.