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Jian-Yang

Quant Dev
China

As a Quantitative Analyst with over five years of experience, I am dedicated to developing and implementing sophisticated quantitative models and trading strategies.

About Me

My academic background, with studies in areas such as Quantitative Finance and Financial Engineering, provided a strong foundation for my expertise in rigorous data analysis, statistical modeling, and algorithmic development. I focus on translating complex market dynamics and vast datasets into actionable trading insights and robust automated systems.

I specialize in areas including time series analysis, the application of machine learning techniques to financial markets, and portfolio optimization. My objective is to leverage advanced mathematical, statistical, and computational methods to solve intricate financial problems and deliver high-performing, data-driven solutions.

Throughout my career, I have collaborated closely with traders, fellow researchers, and software engineers to design, build, and deploy impactful quantitative solutions. In my free time, I enjoy exploring new developments in quantitative finance and machine learning, contributing to open-source projects, and participating in data science competitions to continuously sharpen my analytical and programming skills.

Expertise

  • Proficient in Python (incl. libraries like NumPy, Pandas, Scikit-learn, TensorFlow/PyTorch), C++, SQL, and Rust.
  • Strong capabilities in statistical modeling, hypothesis testing, comprehensive backtesting methodologies, and model validation.
  • Extensive experience working with large-scale financial datasets, market microstructure, and financial data APIs (e.g., Bloomberg, Refinitiv).
  • Passionate about applying cutting-edge academic research and innovative techniques to solve real-world challenges in trading and financial markets.

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