A trading firm is seeking a mid-to-senior Quant Researcher to develop and optimize systematic trading strategies across exchange-traded markets. This role focuses on extracting predictive signals from market data, improving execution logic, and contributing to production-grade algorithmic trading systems in a low-latency environment.
Responsibilities
Key Responsibilities
Alpha & Signal Research
•
Develop predictive trading signals using statistical modeling and machine learning techniques
•
Conduct market microstructure research using tick-level and order-book datasets
•
Design and test systematic strategies across equities, futures, or derivatives
•
Analyze signal decay, feature stability, and regime sensitivity
Backtesting & Validation
•
Build scalable back testing pipelines for strategy evaluation
•
Perform robustness testing across multiple market regimes
•
Detect overfitting risks and improve model generalization
•
Evaluate transaction costs, slippage, and liquidity effects
Execution Optimization
•
Improve execution logic and inventory management models
•
Support enhancements to quoting strategies in electronic markets
•
Collaborate with engineers to deploy production-ready signals
•
Optimize latency-sensitive components where required
Cross-Team Collaboration
•
Work alongside traders to refine strategy hypotheses
•
Partner with engineering teams on implementation workflows
•
Contribute to internal research tools and analytics frameworks
Requirements
MSc or PhD in Mathematics, Statistics, Physics, Computer Science, Financial Engineering, or related quantitative discipline
•
5–8+ years experience in quantitative research or systematic trading environments
•
Strong programming skills in Python
Nice to have
•
Working knowledge of C++ preferred
•
Strong foundation in probability, statistics, optimization, and time-series modeling