About the role
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
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