I am Yufen Chien, I graduated from the Institute of Marketing and Communication Management at National Sun Yat-sen University and currently serve as a data analyst at the Digital Technology Hub of the Taiwan External Trade Development Council (TAITRA). During my tenure, I have demonstrated exceptional project management and cross-department communication skills, frequently leading significant projects. My work primarily focuses on four areas: data analysis, data warehousing, digital transformation, and data product development.

In terms of data analysis, I utilize Tableau for data visualization. Through this, I observed that due to the impact of the war, Taiwan's exports to Ukraine generally declined, except for polyethylene polymers, which showed countertrend growth. This discovery opened a new export channel for Taiwan's chemical industry.

Regarding data warehousing, I established an operational data store (ODS) focused on trade data and constructed a relational data model. I collected raw data through databases, Python web scraping, APIs, and RPA, then used ETL tools for data transformation, cleaning, and computation, finally integrating Tableau to create visual analysis reports. This project reduced our data report delivery time by 70 hours.

In the company's digital transformation project, I introduced the "Data Mart," achieving a training participation rate of 102.9%. Five months later, the company stopped requesting data from the IT department, and employees began using Power BI to connect to the Data Mart for self-service data analysis, enhancing work efficiency and data application flexibility.

For product development, I created a "Global Trade Data Visualization Report" platform, allowing users to easily select the market and industry they wish to observe and instantly obtain relevant dashboards. Previously, it took at least one hour for a colleague to service a customer; now, the customer can request a report in just three minutes, with no manpower or time required from the company, significantly improving work efficiency.

Additionally, during my work period, I self-taught Python and executed a side project, the "Bifinex Lending Rate Prediction Bot." I used the Python web scraping library BeautifulSoup to capture transaction data from the platform and conducted statistical analysis using correlation-weighted averaging and the K-nearest neighbors model, utilizing Pandas for computation and returning results. This project helps users make more advantageous lending decisions.

Before becoming a data analyst, I worked in the marketing field, honing my storytelling skills, presentation abilities, creativity, and problem-solving skills. These skills enabled me to become a communication bridge between the IT department and the business department when I transitioned to a data analyst role. Additionally, I continuously engage in self-learning to enhance my professional capabilities. I look forward to leveraging my past experiences and skills in a new position to create more value for the company.