Quantitative Researcher

3 weeks ago


Bengaluru, Karnataka, India Grizmo Labs Private Limited Full time

Job Title : Quantitative Researcher

Key Responsibilities :


- Design, develop, and implement systematic trading strategies with a focus on Delta 1 and Options, leveraging proprietary and alternative datasets.

- Independently set up and manage robust quantitative research frameworks, including data ingestion, feature engineering, backtesting, and simulation.

- Work closely with trading, engineering, and risk teams to deploy strategies into production environments and ensure ongoing performance monitoring.

- Analyze market microstructure, order book dynamics, and latency-sensitive data to uncover alpha-generating opportunities.

- Conduct statistical modeling, machine learning, and predictive analytics to enhance existing strategies and develop new ones.

- Optimize algorithms and risk models for performance, robustness, and capital efficiency.

- Document and clearly communicate research methodology, assumptions, and outcomes to both technical and non-technical stakeholders.

- Stay up to date with the latest academic and industry research, tools, and techniques.

Required Qualifications :


- 3+ years of hands-on quantitative research experience with a proven record of live trading strategy deployments.

- Bachelors, Masters, or Ph.D. in Mathematics, Statistics, Physics, Computer Science, Engineering, or Financial Engineering from a top-tier institute.

- Advanced proficiency in Python, R, or C++, with strong coding skills for data manipulation, modeling, and performance optimization.

- Deep experience working with large datasets (market data, tick data, alternative data, etc.) and data analysis tools.

- Strong command over quantitative modeling, algorithm development, and risk assessment techniques.

- In-depth understanding of Delta 1 and Options strategies, especially market microstructure, execution models, and high-frequency trading dynamics.

- Ability to clearly present and explain complex research findings to both technical and non-technical Skills :

- Experience with High-Frequency Trading (HFT) or Medium-Frequency Trading (MFT) strategies, particularly in market making or arbitrage.

- Exposure to options pricing models, volatility surfaces, and Greeks management.

- Hands-on knowledge of machine learning techniques, including :

1. Time-series analysis

2. Regression models

3. Ensemble methods

4. Deep learning or neural networks

- Familiarity with cloud-based research infrastructure, data lakes, and real-time data processing pipelines is a plus.

- Comfortable working in a fast-paced, performance-driven trading environment.

(ref:hirist.tech)

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