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 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