Quantitative Researcher
3 weeks ago
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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