Quant Researcher
We are seeking a highly analytical and intellectually curious Quantitative Researcher to join our dynamic and fast-paced team. As a Quant Researcher, you will play a critical role in developing and enhancing systematic trading strategies, conducting rigorous data analysis, and contributing to the firm's alpha generation efforts. This role is ideal for individuals who are passionate about quantitative finance, statistical modeling, and working with large datasets to uncover actionable insights.
Key Responsibilities:
- Design, develop, and implement quantitative models and trading strategies across various asset classes.
- Conduct in-depth research and statistical analysis on large and complex financial datasets.
- Backtest and validate strategies using historical data to ensure robustness and performance.
- Collaborate with portfolio managers, data engineers, and software developers to integrate research into production systems.
- Continuously monitor and refine models based on market behavior and performance metrics.
- Explore and incorporate alternative data sources to enhance predictive power and alpha generation.
Required Qualifications:
- Master's or PhD in a quantitative field such as Mathematics, Statistics, Physics, Computer Science, Engineering, or Financial Engineering.
- Strong programming skills in Python, R, or C++ for data analysis and model development.
- Solid understanding of statistical methods, machine learning techniques, and time-series analysis.
- Experience working with financial data, including equities, derivatives, or fixed income instruments.
- Familiarity with backtesting frameworks and data visualization tools.
- Excellent problem-solving skills and the ability to think critically and independently.
- Strong communication skills, both written and verbal, with the ability to explain complex concepts to non-technical stakeholders.
Preferred Qualifications:
- Prior experience in a quantitative research or trading role at a hedge fund, investment bank, or proprietary trading firm.
- Knowledge of market microstructure and execution algorithms.
- Experience with SQL and working with large-scale databases.
- Exposure to cloud computing platforms and distributed computing environments.
- Familiarity with alternative data sources and data acquisition techniques.
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