Quant Researcher & Trader

About the RoleA 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 ResponsibilitiesAlpha & 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 sensitivityBacktesting & 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 effectsExecution 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 requiredCross-Team Collaboration- Work alongside traders to refine strategy hypotheses- Partner with engineering teams on implementation workflows- Contribute to internal research tools and analytics frameworksRequirementsMSc 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

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