I have worked in multiple technical fields, including quantitative finance, signal processing, data mining, software development, wireless systems engineering, etc.
I am always passionate about new ideas, innovations and technologies, and keep expanding my interests and growing my professional skills.
- Data science: statistical inference, predictive modeling with machine learning methods.
- Statistical signal processing: state and parameter estimation, state space models.
- Data engineering: data pipeline building, Flask RESTful API, data streaming, cleansing, transformation, summary statistics report generation.
- Python data stack: pandas, numpy, scikit-learn, statsmodels, scipy, dask, jupyter notebook, xgboost, etc.
- Data visualization: Matplotlib, Bokeh, Seaborn, Plot.ly, Dash server, Grafana and Excel API.
- Python and C++ application development with objected-oriented design in Linux environment.
- Cloud development: MySQL, Apache Spark (PySpark/SQL/ML), Git, Docker, Jenkins, Linux, AWS.