Quantitative trader

Role: Quant Strategist/Trader
Role Summary:
We are looking for a Quant Strategist – LFT to lead the research, development, and deployment of systematic trading strategies across equity derivatives, index futures/options, and factor-based equity portfolios. This role is ideal for someone with strong quantitative research capabilities, deep understanding of financial markets, and the technical expertise to translate research into production-ready trading systems.
You will work at the intersection of quantitative research, portfolio construction, execution systems, and data infrastructure, with a focus on building scalable low- to mid-frequency strategies.
Key Responsibilities
Quantitative Research & Strategy Development

• Conduct rigorous quantitative research to develop low- to mid-frequency systematic strategies in equity derivatives and cash equities.
• Study academic literature, market microstructure, and alternative data to generate and test new hypotheses.
• Design and implement strategies in:
• Index Futures
• Options (using Greeks, volatility surfaces, liquidity, skew, carry, etc.)
• Factor-based long/short equity portfolios
• Build and evaluate predictive signals using econometric, statistical, and machine learning methods.
• Develop robust portfolio construction frameworks, including factor blending, risk budgeting, and optimization.

Execution & Production Deployment

• Translate research strategies into production-grade code for live deployment.
• Work closely with execution systems to ensure robustness, scalability, and operational efficiency.
• Monitor live strategies, identify anomalies, and improve execution performance.
• Enhance trading systems periodically for latency, stability, and process optimization.

Data & Backtesting Infrastructure

• Maintain and improve proprietary backtesting libraries and research frameworks.
• Collaborate with data engineering teams to onboard new datasets and improve internal databases.
• Ensure data integrity, quality control, and research reproducibility.
• Optimize simulation frameworks for speed, realism, and scalability.

Required Skills & Qualifications

• Solid foundation in multi-factor models, alpha research, and portfolio construction
• Strong understanding of options pricing, derivatives, volatility, and Greeks
• Advanced knowledge of:
• Probability
• Statistics / Econometrics
• Linear Algebra
• Time Series Analysis
• High proficiency in programming (Python required; C++/Java preferred)
• Experience with quantitative research and hypothesis-driven strategy development
• Ability to work with large datasets and production systems
• Familiarity with fundamental and alternative datasets is a strong plus

Preferred Background

• Experience in systematic trading, quantitative finance, or adjacent research-heavy fields
• Prior work in:
• Equity derivatives
• Statistical arbitrage
• Factor investing
• Quantamental strategies
• Exposure to live strategy deployment and trading infrastructure