About the Role:

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:

1. Index Futures

2. Options (using Greeks, volatility surfaces, liquidity, skew, carry, etc.)

3. 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:

1. Probability

2. Statistics / Econometrics

3. Linear Algebra

4. 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:

1. Equity derivatives

2. Statistical arbitrage

3. Factor investing

4. Quantamental strategies

- Exposure to live strategy deployment and trading infrastructure