Role: Quantitative Rates Researcher
Job Type: Contract
Work Mode: Fully Remote
Compensation: $80–$150 per hour
About the Opportunity
We are seeking experienced Quantitative Rates Researchers to contribute to a specialized project focused on evaluating quantitative research and algorithmic trading strategies in fixed-income and interest-rate markets.
In this role, you will assess AI-generated quantitative research, validate trading methodologies, identify statistical and implementation issues, and provide expert feedback to improve the quality and reliability of AI-driven research systems.
Prior AI experience is not required. Robust expertise in quantitative finance, systematic trading, and rates markets is essential.
Key Responsibilities
- Review and evaluate AI-generated quantitative research and trading strategy outputs focused on fixed-income and interest-rate markets.
- Identify and document methodological issues, including lookahead bias, overfitting, data snooping, and unrealistic transaction cost assumptions.
- Evaluate systematic strategy backtesting frameworks, including rates-specific mechanics such as carry, roll-down, and contract roll conventions.
- Assess the statistical rigor of signal construction, factor modeling, alpha research, and strategy validation.
- Review yield curve modeling, relative value trading approaches, and interest-rate trading methodologies.
- Evaluate the accuracy and reliability of quantitative models under realistic market conditions.
- Assess transaction costs, liquidity constraints, and other practical considerations affecting strategy performance.
- Provide detailed written feedback on model assumptions, implementation accuracy, research methodology, and overall strategy soundness.
- Collaborate with project coordinators to clarify findings, communicate recommendations, and resolve methodological questions.
- Contribute to improving research evaluation processes, analytical standards, and quality assurance.
Required Qualifications
- Strong background in quantitative research, quantitative analysis, or quantitative consulting within fixed-income or interest-rate markets.
- Demonstrated experience developing, evaluating, or backtesting systematic rates trading strategies.
- Advanced proficiency in Python or R for quantitative research and data analysis.
- Proficiency with Python libraries such as pandas, NumPy, and SciPy.
- Strong understanding of fixed-income analysis, rates markets, and yield curve modeling.
- Knowledge of carry/roll-down analytics, relative value trading, and systematic strategy research.
- Familiarity with SOFR and Eurodollar instruments, as well as U.S. Treasury futures.
- Strong understanding of statistical validation, factor modeling, and alpha research.
- Ability to identify methodological weaknesses, including lookahead bias, overfitting, and data snooping.
- Understanding of transaction cost analysis, liquidity assessment, and realistic backtesting assumptions.
- Excellent written and verbal communication skills.
- Exceptional attention to detail and strong analytical problem-solving abilities.
Preferred Experience
Experience in one or more of the following environments is highly desirable:
- Hedge funds
- Asset management firms
- Investment banks
- Quantitative trading firms
- Systematic fixed-income or interest-rate strategy research teams
Previous experience reviewing quantitative models, validating trading strategies, or assessing research methodology against industry best practices is an added advantage.
Compensation & Work Arrangement
- Pay Rate: $80–$150 per hour
- Location: Remote
- Engagement Type: Contract-based project
- AI Experience: Not required
How to Apply
Interested candidates with strong quantitative finance expertise and hands-on experience in fixed-income or rates strategy research are invited to share their updated resumes, highlighting relevant experience in systematic trading, backtesting, and quantitative modeling. Share at Email ID :
[email protected] OR Whatsapp: (phone hidden)
📌 Quantitative Rates Researcher (India)
🏢 Kaliper
📍 India