Quantitative Researcher | Remote

Quantitative Rates Researchers, Fixed Income Quants & Systematic Trading Specialists. Remote AI Project

We are seeking experienced Quantitative Rates Researchers, Fixed Income Quants, Systematic Trading Researchers, and Quantitative Analysts to contribute to a remote project focused on evaluating research for an institutional algorithmic trading platform.

You will review quantitative research and trading strategy outputs across fixed income and rates markets, identify methodological weaknesses, assess backtesting quality, and evaluate whether models reflect realistic market conditions.

What You’ll Do

• Review quantitative research and systematic trading strategy outputs focused on fixed income and interest rate markets.
• Evaluate whether research methodology, signal construction, backtesting, and implementation are technically sound.
• Identify issues such as lookahead bias, overfitting, data snooping, survivorship bias, leakage, and unrealistic assumptions.
• Assess transaction cost, liquidity, slippage, execution, and market impact assumptions.
• Review rates-specific mechanics including carry, roll-down, curve positioning, contract rolls, and futures conventions.
• Evaluate statistical significance, robustness, factor construction, and alpha research methodology.
• Identify discrepancies between theoretical strategy logic and actual implementation.
• Review code or quantitative outputs for methodological consistency when relevant.
• Provide detailed written feedback on assumptions, research quality, and implementation fidelity.
• Help refine evaluation standards used to assess quantitative research.

Who Can Apply

Relevant backgrounds include Quantitative Researchers, Quantitative Analysts, Quant Researchers, Quantitative Strategists, and Systematic Researchers.

We also welcome Fixed Income Quantitative Researchers, Rates Quant Researchers, Interest Rate Quants, Fixed Income Strategists, and Rates Strategists.

Systematic trading backgrounds may include Systematic Traders, Algorithmic Traders, Quantitative Traders, Alpha Researchers, and Systematic Portfolio Researchers.

Asset management backgrounds may include Quantitative Portfolio Managers, Fixed Income Portfolio Analysts, Macro Quant Researchers, and Systematic Macro Researchers.

Banking backgrounds may include Rates Quantitative Analysts, Front Office Quants, Electronic Trading Quants, Trading Desk Strategists, and Quantitative Consultants.

Additional relevant backgrounds include Financial Engineers, Derivatives Quants, Risk Quantitative Analysts, and Researchers with strong rates or fixed income expertise.

Requirements

• Professional experience as a quantitative researcher, quantitative analyst, systematic trader, strategist, or consultant with strong fixed income or rates expertise.
• Demonstrated experience building, backtesting, or evaluating systematic trading strategies.
• Strong understanding of fixed income markets, interest rates, yield curves, and relative value.
• Advanced proficiency in Python or R for quantitative research.
• Strong knowledge of backtesting methodology and common research biases.
• Ability to evaluate transaction costs, liquidity constraints, and implementation realism.
• Strong statistical reasoning and attention to detail.
• Excellent written communication skills.
• Comfortable working independently in a remote environment.

Preferred Background

• Professional experience at a hedge fund, investment bank, asset manager, proprietary trading firm, or quantitative research organization.
• Experience researching systematic rates, fixed income relative value, or macro strategies.
• Experience with yield curve models, carry and roll-down analysis, SOFR, Treasury futures, or related instruments.
• Experience reviewing quantitative models, backtests, or research for methodological quality.
• Experience with factor modeling, alpha research, portfolio construction, or risk modeling.
• Experience evaluating strategies under realistic transaction cost and liquidity assumptions.
• Experience with research governance, model validation, or quantitative best-practice review is valuable.

This opportunity is ideal for experienced quantitative researchers who can review a rates strategy, determine whether the signal and backtest are genuinely robust, identify subtle methodological flaws, evaluate whether the strategy could work under real trading conditions, and explain those conclusions clearly. We are a referral partner of the client.