Jingwei Zhou Email and Phone Number

•Cleaned and processed a large dataset comprising 20M observations using the dplyr package in R for data preprocessing. Integrated GIS tools in R with the sf and tmap packages to handle and visualize spatial data, allowing for spatially aware data analysis and mapping. Utilized ggplot2 and gtsummary packages for data summarization and visualization, including tables, box plots, and pie charts.•Merged two datasets by state, county, and census tracts, and conducted normality tests to examine data distribution across geographical levels to understand how geography affects the relationship between variables.•Conducted comprehensive literature reviews and organized research findings in Google Sheets, enhancing the research team's understanding of the field and significantly improving the efficiency and accuracy of data analysis.•Produced a codebook for over 160 variables, enabling swift and precise data interpretation by the research team.

•Utilized SQL to conduct complex queries and data processing from databases, precisely identifying slow-moving products. Collaborated with operations department to develop promotional strategies for these products, optimizing inventory structure and achieving a 5-8% increase in quarterly inventory turnover rates.•Developed intelligent visual report charts using Excel's chart features, enabling automatic generation of daily, weekly, monthly, and yearly visual content upon data import, significantly improving work efficiency. Monitored market trends and product performance using the visual reports to drive data-driven decisions, assisting the operations department in timely adjustments to sales strategies, resulting in an 8% increase in annual sales.•Analyzed key metrics such as the number of new users, growth rates, churn rates, effective member ratios, and retention rates on an e-commerce data analysis platform. Guided page optimization and content layout through data insights, resulting in a 30% increase in page views.•Designed customer profiles based on basic user information and transaction behaviors. Utilized customer profiles and the RFM model to segment users, providing personalized marketing activities for high-value users, enhancing user engagement and increasing user retention rates by 25%.

• Conducted data gathering interviews, helping identify the most profitable customer segments.• Successfully acquired 30+ clients for retail banking products through cold-calling and relationship-building.• Collaborated with top real estate developers, hosting finance-focused conferences and gaining 160 new high net-worth clients.