Location: Shanghai, Hong Kong, Singapore, Abu Dhabi
Key Responsibilities
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Develop and implement statistical models, machine learning algorithms, and quantitative strategies using Python.
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Analyze large datasets (market data, order book data, alternative data) to identify trading signals and opportunities.
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Collaborate with quantitative researchers to backtest, refine, and optimize trading strategies.
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Build and maintain data pipelines for real-time and historical market data processing.
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Conduct exploratory data analysis (EDA) to uncover patterns, anomalies, and predictive features.
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Work with high-performance computing environments to ensure low-latency execution of models.
Required Skills & Qualifications
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Strong proficiency in Python (NumPy, pandas, scikit-learn, SciPy, Jupyter, etc.).
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Experience with quantitative analysis, statistical modeling, and machine learning (time series forecasting, regression, classification, etc.).
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Familiarity with financial markets, trading concepts, and market microstructure (preferred but not required).
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Knowledge of SQL and experience working with large datasets (tick data, order books, etc.).
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Understanding of algorithmic trading, backtesting frameworks, and execution strategies is a plus.
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Experience with distributed computing (Dask, Spark) or high-performance Python (Cython, Numba) is a bonus.
