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Key Responsibilities:
- Develop and implement quantitative trading strategies using cutting-edge techniques in machine learning, deep learning, and alternative data sources.
- Perform rigorous backtesting and analysis of trading strategies to evaluate their performance and risk characteristics.
- Collaborate with the trading team to deploy strategies in live markets, ensuring smooth integration and monitoring.
- Stay abreast of the latest research and developments in quantitative finance and adapt strategies accordingly.
- Contribute to the continuous improvement of the research process, including the development of new tools and methodologies.
- Mentor junior team members and contribute to the knowledge-sharing culture within the team.
Required Qualifications:
- Master's degree or Ph.D. in a quantitative field such as Mathematics, Physics, Statistics, Computer Science, or a related discipline.
- 3+ years of experience in quantitative research or a related field.
- Strong programming skills in Python and proficiency in using machine learning libraries (e.g., scikit-learn, TensorFlow, PyTorch).
- Experience with high-performance computing environments and parallel processing.
- Familiarity with financial markets and instruments, including equities, futures, and options.
- Excellent analytical skills and a strong track record of research and development in quantitative finance.
- Ability to work independently and as part of a team in a fast-paced, dynamic environment.
- Strong communication skills and the ability to present complex ideas clearly and concisely.
Preferred Qualifications:
- Experience in developing and maintaining live trading strategies.
- Knowledge of graph neural networks and their application in financial markets.
- Experience with alternative data sources and their integration into quantitative models.
- Familiarity with risk management techniques and tools.
- A strong network within the quantitative finance community.
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