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