Xperteez Technology
USD 80–150 / hour
As the advert gives it
Role Title: Quantitative Rates Researcher
Role Type: Contract
Location: Remote
Required Skills:
Python
R
Pandas
Numpy
Scipy
Fixed income analysis
Rates markets expertise
Systematic strategy backtesting
Yield curve modeling
Carry/roll-down analytics
Relative value trading
Sofr/eurodollar instruments
Treasury futures
Statistical rigor
Factor modeling
Alpha research
Transaction cost analysis
Liquidity assessment
Model validation
Written communication
Attention to detail
Quantitative research
Data analysis
Reviewing methodological issues (lookahead bias, overfitting, data snooping)
Collaborative communication
In this role, you'll apply your expertise to help train next-generation AI systems. Your work will shape how models learn, reason, and perform through high-quality, real-world input. No prior experience in AI is required - your domain knowledge is what matters.
Scope of Work:
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, data snooping, and unrealistic transaction cost assumptions
Evaluate the accuracy of backtesting frameworks, especially with respect to rates-specific mechanics like carry/roll-down and contract roll conventions
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 written and verbal communication
Contribute to the refinement of research evaluation processes for greater accuracy and relevance
Preferred 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, SOFR/Eurodollar instruments, and Treasury futures
Comfort evaluating research under real-world trading conditions, including transaction costs and liquidity constraints
Exceptional attention to detail and ability to articulate complex quantitative findings in clear, concise written feedback
Prior experience assessing or reviewing models for compliance with best practices in quantitative finance is a plus
Originally posted on Himalayas
