Senior Quantitative Researcher

We are seeking an experienced and innovative Senior Quantitative Researcher to lead the research, development, and implementation of cutting-edge trading strategies and mathematical models. In this role, you will analyze massive financial datasets, identify market inefficiencies, and build robust algorithmic trading strategies. You will collaborate closely with Quantitative Developers, Portfolio Managers, and Data Engineers to push strategies from concept into live production trading environments.

Responsibilities

• Alpha Generation & Strategy Development: Research, develop, and backtest systematic, automated trading strategies (stat-arb, market making, momentum, trend-following, or execution algorithms) across global financial markets.
• Quantitative Modeling: Construct, refine, and validate statistical, mathematical, and machine learning models to analyze market microstructure, pricing dynamics, and risk factors.
• Large-Scale Data Analysis: Clean, process, and feature-engineer massive structured and unstructured financial datasets (tick-level market data, order book dynamics, alternative data).
• Portfolio & Risk Management: Design dynamic portfolio optimization frameworks, exposure controls, and risk-management protocols to maximize risk-adjusted returns (Sharpe/Sortino ratios).
• Production Deployment: Partner with Quantitative Developers and Systems Engineers to translate research models into low-latency C++/Python production trading systems.
• Leadership & Mentorship: Guide junior researchers, lead research initiatives, and drive innovation in research methodologies and software tools.

Qualifications

• Education: Ph.D. or Master’s degree in a quantitative discipline (e.g., Mathematics, Statistics, Physics, Computer Science, Financial Engineering, or Electrical Engineering).
• Experience: 4+ years of hands-on experience as a Quantitative Researcher at a hedge fund, proprietary trading firm, or asset manager with a proven track record of strategy development.
• Programming Skills: Advanced proficiency in Python (Pandas, NumPy, SciPy, PyTorch/TensorFlow) or C++ for high-performance statistical modeling and simulation.
• Mathematical Mastery: Deep grounding in probability theory, linear algebra, time-series analysis, stochastic calculus, machine learning, and optimization techniques.
• Data & Systems: Experience working with tick data, order book mechanics, and high-performance distributed computing frameworks.

Preferred Qualifications

• Direct experience generating profitable alpha in high-frequency trading (HFT) or medium-frequency trading (MFT).
• Expertise in alternative data sources (sentiment data, satellite imagery, Web/NLP data).
• Strong understanding of exchange connectivity, FIX protocol, and low-latency execution pipelines.