About the Role
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.
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
- Working knowledge of C++ preferred
- Strong foundation in probability, statistics, optimization, and time-series modeling
- Experience working with market data at scale