As a Data Scientist in the AI Garage of Capgemini Invent, I work with technical as well as subject matter experts to develop data-driven solutions and products. I am particularly interested in machine learning, especially its applications in the natural language processing (NLP). Being in-fluent in both Python and R and close to academic discussions, I attempt to identify the best strategies for enterprises to turn internal and external data into valuable analytical assets and distill the signals from noises.
Since I joined Capgemini, I have been working in the banking and the pharmaceutical industry for standardizing the analytical pipeline.
My recent work includes:
– Designing and implementing a reporting tool for a leading German bank, which significantly reduces manual efforts and saves cost
– Functioning as NLP expert in a pharmaceutical company in Germany to build a plausible ML/NLP pipeline
I previously worked in the academic field and had important operating role in algorithmic design of data-driven social science projects, incl. text classification and topic modeling. I am particularly interested in the intersection between social science and statistics.
Previously, I have studied at University of Konstanz and Yale University, and joined research teams and led training and tutorials in both institutions. For instance, I created a tutorial for NLP at Yale University and led a training at its graduate school.
I am fluent in Chinese, English, and German. In his spare time, he is a passionate swimmer and blogger.